Network administrator jobs in Santa Rosa, CA - 565 jobs

A leading financial institution seeks a Market Executive in San Francisco to manage relationships within the Software Technology sector and lead banking teams. The candidate will focus on innovative startups and require 15+ years of experience in account management within a Commercial Bank. This role also demands strong communication and problem-solving skills. A competitive salary and benefits are offered for this full-time position, with an emphasis on industry trends and client acquisition. #J-18808-Ljbffr

About Us: Ambience Healthcare is the leading AI platform for documentation, coding, and clinical workflow, built to reduce administrative burden and protect revenue integrity at the point of care. Trusted by top health systems across North America, Ambience's platform is live across outpatient, emergency, and inpatient settings, supporting more than 100 specialties with real-time, coding-aware documentation. The platform integrates directly with Epic, Oracle Cerner, athenahealth, and other major EHRs. Founded in 2020 by Mike Ng and Nikhil Buduma, Ambience is headquartered in San Francisco and backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, Kleiner Perkins, and other leading investors. Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers, technologists, clinicians, and innovators. The Role: We're looking for a Machine Learning Infrastructure Engineer to join our AI Platform team. This is a high-leverage role focused on building and scaling the core infrastructure that powers every AI system at Ambience. You'll work closely with our ML, data, and product teams to develop the foundational tools, systems, and workflows that support rapid iteration, robust evaluation, and production reliability for our LLM-based products. Our Engineering roles are hybrid in our SF office 3x/wk. What You'll Do: You have 5+ years of experience as a software engineer, infrastructure engineer, or ML platform engineer You've worked directly on systems that support ML research or production workloads - whether training pipelines, evaluation systems, or deployment frameworks You write high-quality code (we primarily use Python) and have strong engineering and systems design instincts You're excited to work closely with ML researchers and product engineers to unblock them with better infrastructure You're pragmatic and care deeply about making tools that are reliable, scalable, and easy to use You thrive in fast-paced, collaborative environments and are eager to take ownership of ambiguous problems Who You Are: Design, build, and maintain the infrastructure powering ML model training, batch inference, and evaluation workflows Improve internal tools and developer experience for ML experimentation and observability Partner with ML engineers to optimize model deployment and monitoring across clinical workloads Define standards for model versioning, performance tracking, and rollout processes Collaborate across the engineering team to build reusable abstractions that accelerate AI product development Drive performance, cost efficiency, and reliability improvements across our AI infrastructure stack Pay Transparency We offer a base compensation range of approximately $200,000-300,000 per year, exclusive of equity. This intentionally broad range provides flexibility for candidates to tailor their cash and equity mix based on individual preferences. Our compensation philosophy prioritizes meaningful equity grants, enabling team members to share directly in the impact they help create. Are you outside of the range? We encourage you to still apply: we take an individualized approach to ensure that compensation accounts for all of the life factors that matter for each candidate. Being at Ambience: An opportunity to work with cutting edge AI technology, on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients Dedicated budget for personal development, including access to world class mentors, advisors, and an in-house executive coach Work alongside a world-class, diverse team that is deeply mission aligned Ownership over your success and the ability to significantly impact the growth of our company Competitive salary and equity compensation with benefits including health, dental, and vision coverage, quarterly retreats, unlimited PTO, and a 401(k) plan Ambience is committed to supporting every candidate's ability to fully participate in our hiring process. If you need any accommodations during your application or interviews, please reach out to our Recruiting team at accommodations@ambiencehealth.com. We'll handle your request confidentially and work with you to ensure an accessible and equitable experience for all candidates. #J-18808-Ljbffr

A pioneering AI startup in San Francisco is looking for an experienced individual to build infrastructure for deploying personalized AI models. The role demands a strong understanding of machine learning technology and a passion for enabling user-controlled AI solutions. Ideal candidates will thrive in fast-paced environments and contribute to impactful AI development. The company offers competitive compensation, equity, and a significant role in shaping the future of AI. #J-18808-Ljbffr

David AI is the first audio data research company. We bring an R&D approach to data-developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human-it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in. David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we've brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors. Our team is sharp, humble, ambitious, and tight-knit. We're looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI. About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world's first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As our Founding Machine Learning Infrastructure Engineer at David AI, you will build and scale the core infrastructure that powers our cutting-edge audio ML products. You'll be leading the development of the systems that enable our researchers and engineers to train, deploy, and evaluate machine learning models efficiently. In this role, you will Design and maintain data pipelines for processing massive audio datasets, ensuring terabytes of data are managed, versioned, and fed into model training efficiently. Develop frameworks for training audio models on compute clusters, managing cloud resources, optimizing GPU utilization, and improving experiment reproducibility. Create robust infrastructure for deploying ML models to production, including APIs, microservices, model serving frameworks, and real-time performance monitoring. Apply software engineering best practices with monitoring, logging, and alerting to guarantee high availability and fault‑tolerant production workloads. Translate research prototypes into production pipelines, working with ML engineers and data teams to support efficient data labeling and preparation. and optimization techniques to enhance infrastructure velocity and reliability. Your background looks like 5+ years of backend engineering with 2+ years ML infrastructure experience. Hands‑on experience scaling cloud infrastructure and large‑scale data processing pipelines for ML model training and evaluation. Proficient with Docker, Kubernetes, and CI/CD pipelines. Proven ML model deployment and lifecycle management in production. Strong system design skills optimizing for scale and performance. Proficient in Python with deep Kubernetes experience. Bonus points if you have Experience with feature stores, experiment tracking (MLflow, Weights and Biases), or custom CI/CD pipelines. Familiarity with large‑scale data ingestion and streaming systems (Spark, Kafka, Airflow). Proven ability to thrive in fast‑moving startup environments. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Benefits Unlimited PTO. Top‑notch health, dental, and vision coverage with 100% coverage for most plans. FSA & HSA access. 401k access. Meals 2x daily through DoorDash + snacks and beverages available at the office. Unlimited company‑sponsored Barry's classes. #J-18808-Ljbffr

This is a job that we are recruiting for on behalf of one of our customers. To apply, speak to Jack. He's an AI agent that sends you unmissable jobs and then helps you ace the interview. He'll make sure you are considered for this role, and help you find others if you ask. Machine Learning Infrastructure Engineer Company Description: Early-stage private AI platform Job Description: Build the core infrastructure to serve thousands, then millions, of private, personalized AI models at scale. This role involves optimizing model serving performance for low latency and cost, and integrating a TEE-based privacy stack to ensure user data and models are exclusively accessible by the user, not even the company. Drive the foundational systems for a new era of personal AI. Location: San Francisco, USA Why this role is remarkable: Pioneer the infrastructure for truly private, personal AI models, ensuring user data remains confidential. Join an early-stage, well-funded startup backed by top-tier VCs and leading AI experts. Make a massive impact on the future of AI, helping to keep humans empowered in a post-AGI world. What you will do: Build infrastructure for deploying thousands to millions of personalized finetuned models. Monitor and optimize in-the-wild model serving performance for low latency and cost. Integrate with a TEE-based privacy stack to guarantee user data and model confidentiality. The ideal candidate: Deep understanding of the machine learning stack, including transformer optimization and GPU performance. Ability to execute quickly in a fast-paced, early-stage startup environment. A missionary mentality, passionate about ensuring AI works for people. How to Apply: To apply for this job speak to Jack, our AI recruiter. Step 1. Visit our website Step 2. Click 'Speak with Jack' Step 3. Login with your LinkedIn profile Step 4. Talk to Jack for 20 minutes so he can understand your experience and ambitions Step 5. If the hiring manager would like to meet you, Jack will make the introduction #J-18808-Ljbffr

About AngelList We exist to accelerate innovation. We do this by giving more people the opportunity to participate in the venture economy by building the financial infrastructure that makes it possible for more people to invest in world-changing startups. We also build tools for startup founders that help them run their operations, so they can focus on building their company. AngelList is the nexus of venture capital and the startup community. We support over $171B+ assets on our platform, and we've driven capital to over 13,000 startups. 57% of top-tier U.S. VC deals involve investors on AngelList. While our scale is large, our ambitions are even larger - we're innovating on the infrastructure for venture and individual investors and the startups they invest in. Come build with us! About the Role We're looking for an IT Engineer to join our team on a contract basis, reporting directly to our IT Lead. You'll own the execution of critical IT workstreams across AngelList and our subsidiary companies, taking full responsibility for delivery while operating within established systems and priorities. This role is ideal for someone who thrives on autonomy, can run independently after ramping, and takes pride in reliable execution over strategic planning. Responsibilities Own day-to-day IT operations, including employee onboarding, offboarding, and access management across Google Workspace, Rippling, 1Password, and Slack. Troubleshoot and resolve IT issues independently, serving as a reliable resource for employees. Execute on MDM and endpoint management, maintaining security policies and device compliance. Manage SaaS platforms, including license tracking, access reviews, and vendor coordination. Maintain and improve IT documentation, playbooks, and runbooks. Own cross-functional projects as assigned, coordinating with engineering, security, and ops teams. Manage office IT infrastructure and AV equipment as needed. What We're Looking For 3-5+ years of experience in IT operations, systems administration, or similar roles. Hands‑on experience with Google Workspace, Slack, and common SaaS tools. Solid understanding of identity and access management. Strong troubleshooting instincts and a bias toward solving problems without escalation. Reliable and organized - someone who follows through without needing reminders. Clear communicator who can work across teams and explain technical issues simply. Experience in automation and scripting to reduce manual work and improve efficiency. Experience with Rippling, Slack Grid or n8n.io is a plus. If you don't tick every box above, we'd still encourage you to apply. We're building a diverse team whose skills balance and complement one another. Office Location and Expectations AngelList has offices in two hub cities: This role is based in our San Francisco office. You will be expected to come in three times a week, usually Tuesdays, Wednesdays, and Thursdays, with some flexibility for occasional Mondays or Fridays. The role also includes light after‑hours support to set up IT for occasional evening events. If you need to be offline at 5 PM every day, this won't be the right fit. Compensation: $80+ an hour, 40-45 hours a week. Working at AngelList: At AngelList, we are united in our purpose to accelerate innovation and build the future of private markets. Our beliefs and values shape how we work, collaborate, and create impact. If the below resonate, we'd love to have you with us. *Beliefs: ************************** *Values & Leadership Expectations: ************************* AngelList is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #J-18808-Ljbffr

A pioneering tech company in San Francisco is seeking a Robotics Engineer who excels in system-level debugging and end-to-end feature delivery for autonomous trucks. The successful candidate will develop and validate autonomy features, lead technical deployments, and collaborate across various teams. Requirements include 2+ years of software development experience and strong programming skills in modern languages. A role involving occasional travel to customer sites is also included. #J-18808-Ljbffr

At Truth Systems, we're building the only trust and safety software any organization will ever need. A protection layer for every individual. We're laying that foundation with AI Governance. Our product Charter is an agent that monitors and flags misuse of AI in line with firm policies and client rules in real time. We're building always-on, real-time systems that keep people safe and organizations compliant without slowing down their work. We are: Small and well-funded. We've raised $4M from world-class investors like Gradient Ventures, Lightspeed, The Legaltech Fund, Y Combinator, and Pear VC. We are currently a team of 4. We are hiring thoughtfully, with ~3 people in the next 6 months. Intensely trustful + high ownership. We optimize for impact per person by requiring high ownership from each team member. We hire experts, ambitious problem-solvers, and generally unstoppable people, and we place a lot of trust in them. We prefer short (or no) meetings, full autonomy, and individualized schedules. Your Mission Over the next 12-18 months, you will embed with customers to help firms navigate and uncover risk surfaces within their organizations. This role blends engineering and customer empathy. You'll work directly with clients to understand workflows, translate them into software, and ensure successful adoption. Outcomes Customer integrations from 0 → 1. Lead deployments of our agents and backend systems in live customer environments. Deliver reliable, secure, and fast integrations. Feedback-driven development. Translate client insights into product improvements and new features. Influence our roadmap through real-world usage. Customer Partnership: Collaborate deeply with clients to identify their pain points, propose solutions, and deliver measurable value. Travel for Deployment and Collaboration: Travel to meet customers across the U.S. (e.g., NYC, Atlanta, Chicago, Seattle, Ohio, and more) for implementations, feedback sessions, and training. Competencies Technical and hands-on: You've spent 1+ years building real products in production - shipping code, wrestling with weird APIs, and making things work in messy, real-world stacks. Full-stack curious: You're fluent in TypeScript/JavaScript (React or Next.js for lightweight UIs) and comfortable with at least one backend language like Python for integrations and automations. Deeply empathetic (must be): Both our team and our customers require empathetic and low-ego people. Some of our users' careers depend on our product being ‘right', so trusting and listening to them is our most important skill. Independent and process building (must be): We don't have a lot of structure. You'll build many processes and set standards yourself, and everyone we hire after you will follow them. Adventurous: You're comfortable with the unknown, love building new experiences, and don't mind travel when it helps you get closer to the problem. Our team's roots span 4+ continents - we like working (and learning) with people from everywhere. Why Join Truth Systems Autonomy: You'll have full ownership of what you build. We trust you to make the right calls, set your own pace, and push projects from idea to production without red tape. Output-focused, not input-focused: We care about impact, not hours. Now that is not to say there will not be days when hours don't get long, but you'll be judged by what you deliver and how it moves the needle - not how long you sit in front of a screen. Cutting-edge meets meaningful: You'll be working at the edge of AI - designing systems that redefine how humans interact with intelligence. At Truth Systems, we care deeply about helping knowledge workers trust AI and move them toward safer, more responsible, and transparent use. Logistics Salary: $170K-$250K Equity: 0.3-1% Location: In-person in San Francisco, with regular travel to customer sites across the U.S. Perks: Meals, housing/relocation, equipment, and benefits included Work Authorization: We cannot sponsor visas at this time #J-18808-Ljbffr

About the team The OpenAI for Government team is a dynamic, mission-driven group leveraging frontier AI to transform how governments achieve their missions. Our team works to empower public servants with secure, compliant AI tools (e.g., ChatGPT Enterprise, ChatGPT Gov) and mission-aligned deployments that meet government technical requirements with strong reliability and safety. About the role Forward Deployed Engineers (FDEs) lead complex deployments of frontier models in production. You will embed with our most strategic government and public sector customers-where model performance matters, delivery is urgent, and ambiguity is the default. You'll map their problems, structure delivery, and ship fast. This includes scoping, sequencing, and building full-stack solutions that create measurable value, while driving clarity across internal and external teams. You will work directly with defense, intelligence, and federal stakeholders as their technical thought partner, guiding adoption, maximizing mission impact, and ensuring successful deployments at scale. Along the way, you'll identify reusable patterns, codify best practices, and share field signal that influences OpenAI's roadmap. This role is based in Washington DC, Seattle or San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required, including on-site work with customers. In this role you will Own technical delivery across multiple government deployments, from first prototype to stable production. Deeply embed with public sector customers to design and build novel applications powered by OpenAI models. Enable successful deployments across customer environments by delivering observable systems spanning infrastructure through applications. Prototype and build full-stack systems using Python, JavaScript, or comparable stacks that deliver real mission impact. Proactively guide customers on maximizing business and operational value from their applications. Forge and manage relationships with customer leadership and stakeholders, ensuring successful deployment and scale. Scope work, sequence delivery, and remove blockers early-making trade-offs between scope, speed, and quality. Contribute directly in the code when clarity or momentum depends on it. Codify working patterns into tools, playbooks, or building blocks others can use. Share field feedback with Research and Product to influence model and product development. Keep teams moving through clarity, judgment, and consistent follow-through. You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience, ideally in customer-facing or government environments. Active TS/SCI clearance or equivalent Have scoped and delivered complex systems in fast-moving or ambiguous contexts. Write and review production-grade code across frontend and backend, using Python, JavaScript, or similar stacks. Are familiar with cloud deployment models (Azure, AWS), Kubernetes, Terraform, and related infrastructure. Have experience building or deploying systems powered by LLMs or generative models, and understand how model behavior affects product experience. Simplify complexity, make fast, sound decisions under pressure, and communicate clearly across technical and non-technical audiences. Spot risks early, adjust without slowing down, and model calm judgment when stakes are high. Are humble, collaborative, and eager to help others with empathy. Operate with high horsepower, thrive in dynamic environments, and can ruthlessly prioritize across multiple projects. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI's Aff… Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. #J-18808-Ljbffr

Role As a distributed systems engineer, you'll work across the stack to solve problems as they come up and help build Archil volumes. You'll have significant influence over the technical and product direction. We'll expect you to be able to: Be oncall for a production system to help our customers if anything goes wrong. Build out never-before-seen capabilities in a storage service Design distributed systems interactions for atomicity and idempotency Deploy infrastructure and generalize infrastructure across different clouds Operate through changing customer requirements with lots of ambiguity Who are you? You have 3+ years of experience building and operating distributed systems (flexible). Ideally, you've worked at a startup before, so you know how chaotic this time can be. You've successfully resolved disagreements at work before, and you understand that the highest priority is helping our customers - not being right. You're comfortable debugging problems that occur as a result of failures in multiple, different systems, using tools like metrics and logs. You've been paged at 3am to solve a complex production issue before. You're knowledgeable about distributed systems: you get how consensus works, you know how to scale systems, and you know what pitfalls in API design to avoid. You're familiar with how to optimize the performance of a system, including a general sense of how much latency different operations take, and what kind of bottlenecks could lead to a reduction in potential throughput. Most of all, you know how computers work from the silicon up. Someone once asked you in an interview “what happens when you go to Google.com”, and there wasn't enough time in the interview to talk about all of the steps. Why join us? By building the highest-performance, simplest storage product in the cloud, we have a great chance of changing how the world builds the next-generation of applications (and with AI, more applications will be written in the next 5 years than ever before). We'd love for your to be a part of our journey. How to join? Show us that you're knowledgeable about the space that we're working in on your application. It's up to you how you do this, but one potential way is by answering one of the following questions: How do you think our system works? What do you think our biggest technical challenge is? What would make our system not work? About Archil Archil is on a mission to change how developers build applications in the cloud, by building the next, default storage platform in the cloud. Over the past 15 years, S3 has become the default way to store inactive data sets in the cloud, but the next-generation of AI and analytics applications need to actively process more data than ever before. We're solving this problem by building the first Volume storage product that's as fast as EBS, infinitely scaleable like S3, and connects to existing data sets in S3 and other repositories. Our customers choose Archil because this architecture radically simplifies how they think about working with their data (every application becomes stateless, no cold-start latencies, and no need to worry about checkpointing or backup). Hacker News agrees. Hunter, the founder, has 10 years of experience building and operating cloud storage, including helping to launch Amazon's EFS product and working on bleeding-edge storage at Netflix. He started the company after working with hundreds of customers across these roles, and identifying a need for a new kind of storage product. We're fully in-person in San Francisco. If you're also someone interested in distributed systems, completely focused on how to make customers successful, and interested in solving really big technical challenges, we'd love for you to join us. #J-18808-Ljbffr

A leading AI research company in New York seeks a Machine Learning Systems Engineer to build cutting-edge systems for training AI models. This role involves developing critical algorithms, improving system performance, and collaborating with a dynamic research team. Ideal candidates have a strong software engineering background and care about the societal impacts of AI technology. The expected salary range is $300,000 - $405,000 USD, with a hybrid work policy requiring 25% in-office presence. #J-18808-Ljbffr

A cutting-edge AI startup in San Francisco is seeking a Machine Learning Engineer. In this role, you will build and improve core ML systems that drive custom model training platforms. You will lead projects from data intake to model delivery, creating robust tools and ensuring model performance. The ideal candidate has experience in AI model training with PyTorch, data processing, and creating benchmarks. Offering competitive salaries within a range of $220,000 to $320,000, plus equity and benefits. #J-18808-Ljbffr

A leading technology company based in San Francisco is looking for a creative engineer to enhance the iOS and iPadOS user experience on the Notifications and Focus team. Responsibilities include defining, designing, and implementing innovative features, fixing bugs, and improving performance. The ideal candidate should hold a Bachelor in Computer Science, demonstrate ownership, communication skills, and experience with UIKit or SwiftUI. Competitive compensation and comprehensive benefits are offered, including employee stock programs. #J-18808-Ljbffr

About Us: Ambience Healthcare is the leading AI platform for documentation, coding, and clinical workflow, built to reduce administrative burden and protect revenue integrity at the point of care. Trusted by top health systems across North America, Ambience's platform is live across outpatient, emergency, and inpatient settings, supporting more than 100 specialties with real-time, coding‑aware documentation. The platform integrates directly with Epic, Oracle Cerner, athenahealth, and other major EHRs. Founded in 2020 by Mike Ng and Nikhil Buduma, Ambience is headquartered in San Francisco and backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, Kleiner Perkins, and other leading investors. Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers, technologists, clinicians, and innovators. The Role: We're looking for a Machine Learning Infrastructure Engineer to join our AI Platform team. This is a high-leverage role focused on building and scaling the core infrastructure that powers every AI system at Ambience. You'll work closely with our ML, data, and product teams to develop the foundational tools, systems, and workflows that support rapid iteration, robust evaluation, and production reliability for our LLM‑based products. Our engineering roles are hybrid - working onsite at our San Francisco office three days per week. What You'll Do: You have 5+ years of experience as a software engineer, infrastructure engineer, or ML platform engineer You've worked directly on systems that support ML research or production workloads - whether training pipelines, evaluation systems, or deployment frameworks You write high-quality code (we primarily use Python) and have strong engineering and systems design instincts You're excited to work closely with ML researchers and product engineers to unblock them with better infrastructure You're pragmatic and care deeply about making tools that are reliable, scalable, and easy to use You thrive in fast-paced, collaborative environments and are eager to take ownership of ambiguous problems Who You Are: Design, build, and maintain the infrastructure powering ML model training, batch inference, and evaluation workflows Improve internal tools and developer experience for ML experimentation and observability Partner with ML engineers to optimize model deployment and monitoring across clinical workloads Define standards for model versioning, performance tracking, and rollout processes Collaborate across the engineering team to build reusable abstractions that accelerate AI product development Drive performance, cost efficiency, and reliability improvements across our AI infrastructure stack Pay Transparency We offer a base compensation range of approximately $200,000-300,000 per year, with the addition of significant equity. This intentionally broad range provides flexibility for candidates to tailor their cash and equity mix based on individual preferences. Our compensation philosophy prioritizes meaningful equity grants, enabling team members to share directly in the impact they help create. If your expectations fall outside of this range, we still encourage you to apply-our approach to compensation considers a range of factors to ensure alignment with each candidate's unique needs and preferences. Being at Ambience: An opportunity to work with cutting edge AI technology, on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients Dedicated budget for personal development, including access to world class mentors, advisors, and an in‑house executive coach Work alongside a world‑class, diverse team that is deeply mission aligned Ownership over your success and the ability to significantly impact the growth of our company Competitive salary and equity compensation with benefits including health, dental, and vision coverage, quarterly retreats, unlimited PTO, and a 401(k) plan Ambience is committed to supporting every candidate's ability to fully participate in our hiring process. If you need any accommodations during your application or interviews, please reach out to our Recruiting team at accommodations@ambiencehealth.com. We'll handle your request confidentially and work with you to ensure an accessible and equitable experience for all candidates. #J-18808-Ljbffr

Build the infrastructure to serve personal AI models privately and at scale. We're building the first truly private, personal AI - one that learns your skills, judgment, and preferences without big tech ever seeing your data. Our core ML systems challenge: how do we serve the world's best personal model, at low cost and high speed, with bulletproof privacy? What you'll do Build the infrastructure that lets us create & deploy thousands and eventually millions of personalized finetuned models for our customers Monitor & optimize in-the-wild model serving performance to hit low latency & cost Interface with the TEE-based privacy stack that lets us guarantee user data & models can only be seen & used by the user-not even us-and integrate the privacy architecture with the finetuning & inference code You have A deep understanding of the machine learning stack. You can dive into the details of how transformers work & performance optimization techniques for them. You have a mental model of GPUs sufficient to reason about performance from first principles. You can drill down from ML code to metal. Ability to execute quickly. We ship fast and fail fast so we can win faster. The challenge of human relevance in a post-AGI world isn't going to solve itself. A missionary mentality. We're a mission-driven company, looking for mission-first people. If you're passionate about ensuring AI works for people (and not the other way around), you've come to the right place. Ready to roll up your sleeves. We're an early stage startup, so we're looking for someone who can wear many hats. Experience you may have Work at a fast-paced AI startup, or top AI lab Experience deploying ML systems at scale. You might have worked with frameworks like vLLM, S-LoRA, Punica, or LoRAX. Experience with privacy-first infrastructure. You're familiar with confidential computing & ability to reason about both technical and real-world confidentiality and security. You may have worked with secure enclaves, TEEs, code measurement & remote attestation, Nvidia Confidential Computing, Intel TDX or AMD SEV-SNP, or related confidential computing technologies. We encourage speculative applications; we expect many strong candidates will have different experience or unconventional backgrounds. What we offer Generous compensation and early stage equity. We're competitive with the top startups, because we believe the best talent deserves it. World-class expertise. We're based in top AI research hubs in San Francisco and London. We're backed by AI experts like Juniper Ventures, Seldon Lab, and angels at Anthropic and Apollo Research. You'll have access to some of the best AI expertise in the world. Massive impact. Our mission is to keep people in the economy well after AGI. You'll help shift the trajectory of AI development for the better, helping break the intelligence curse and prevent gradual disempowerment to keep humans in control of the future. About Workshop Labs We're building the AI economy for humans. While everyone else tries to automate the world top-down, we believe in augmenting people bottom-up. Our team previously created evals used by Open AI, completed frontier AI research at MIT/Cambridge/Oxford, worked in Stuart Russell's lab, and led product verticals at high growth startups. The essay series The Intelligence Curse has been covered in TIME, The New York Times, and AI 2027. Our vision is for everyone to have a personal AI aligned to their goals and values, helping them stay durably relevant in a post-AGI economy. As a public benefit corporation, we have a fiduciary duty to ensure that as AI becomes more powerful, humans become more empowered, not disempowered or replaced. We're an early stage startup, backed by legendary investors like Brad Burnham and Matt McIlwain, visionary product leaders like Jake Knapp and John Zeratsky, philosopher-builders like Brendan McCord, and top AI safety funds like Juniper Ventures. Our investors were early at Anthropic, Slack, Prime Intellect, DuckDuckGo, and Goodfire. Our advisors have held senior roles at Anthropic, Google DeepMind, and UK AISI. #J-18808-Ljbffr

A fast-growing tech company based in San Francisco seeks an experienced IT Engineer for contract work. You will manage IT operations, leading employee onboarding and troubleshooting. Candidates should have 3-5 years of experience in IT roles, with skills in Google Workspace and troubleshooting. The position requires reliable execution and communication skills. You will work in the office three days a week, participating in an innovative tech culture that values diversity and collaboration. #J-18808-Ljbffr

A technology firm focused on AI safety is seeking a candidate for a mission-driven role that melds engineering with customer empathy. You will be responsible for leading client integrations of trust and safety software, ensuring successful product adoption while also translating client feedback into actionable improvements. This in-person role is based in San Francisco and includes regular travel across the U.S. Competitive salary and equity are offered. #J-18808-Ljbffr

A cloud storage technology company in San Francisco is looking for a Distributed Systems Engineer to work across the stack in building innovative storage solutions. You will be oncall for production systems and will design distributed systems to meet customer needs. The ideal candidate has over 3 years of experience in distributed systems, problem solving skills, and is passionate about enhancing customer experiences. Join us in our mission to revolutionize cloud storage with the next generation of applications. #J-18808-Ljbffr

Machine Learning Systems Engineer, Research ToolsAbout Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: You want to build the cutting-edge systems that train AI models like Claude. You're excited to work at the frontier of machine learning, implementing and improving advanced techniques to create ever more capable, reliable and steerable AI. As an ML Systems Engineer on our Research Tools team, you'll be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. Your work will directly enable breakthroughs in AI capabilities and safety. You'll focus obsessively on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible. You're energized by the challenge of supporting and empowering our research team in the mission to build beneficial AI systems. Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models. You'll be responsible for improving the speed, reliability, and ease-of-use of these systems. You may be a good fit if you: Have 2+ years of software engineering experience Like working on systems and tools that make other people more productive Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: Python Implementing LLM finetuning algorithms, such as RLHF Representative projects: Profiling our reinforcement learning pipeline to find opportunities for improvement Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline Making changes to our finetuning systems so they work on new model architectures Building instrumentation to detect and eliminate Python GIL contention in our training code Diagnosing why training runs have started slowing down after some number of steps, and fixing it Implementing a stable, fast version of a new training algorithm proposed by a researcher Deadline to apply:None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: $300,000 - $405,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage:Learn aboutour policy for using AI in our application process Create a Job Alert Interested in building your career at Anthropic? Get future opportunities sent straight to your email. Apply for this job indicates a required field First Name * Last Name * Email * Phone Resume/CV Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf (Optional) Personal Preferences * How do you pronounce your name? Website Publications (e.g. Google Scholar) URL Are you open to working in-person in one of our offices 25% of the time? * Select... When is the earliest you would want to start working with us? Do you have any deadlines or timeline considerations we should be aware of? AI Policy for Application * Select... We believe that AI will have a transformative impact on the world, and we're seeking exceptional candidates who collaborate thoughtfully with Claude to realize this vision. At the same time, we want to understand your unique skills, expertise, and perspective through our hiring process. We invite you to review our AI partnership guidelines for candidates and confirm your understanding by selecting “Yes.” Why Anthropic? * Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.) Additional Information * Add a cover letter or anything else you want to share. LinkedIn Profile Please ensure to provide either your LinkedIn profile or Resume, we require at least one of the two. Are you open to relocation for this role? * Select... What is the address from which you plan on working? If you would need to relocate, please type "relocating". Have you ever interviewed at Anthropic before? * Select... Do you have 8 or more years of software engineering experience? * Select... Do you have experience building and maintaining data processing pipelines or infrastructure at scale? * Select... 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As set forth in Anthropic's Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service. An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense. An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985. Select... 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Disabilities include, but are not limited to: Alcohol or other substance use disorder (not currently using drugs illegally) Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS Blind or low vision Cancer (past or present) Cardiovascular or heart disease Celiac disease Cerebral palsy Deaf or serious difficulty hearing Diabetes Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders Epilepsy or other seizure disorder Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome Intellectual or developmental disability Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD Missing limbs or partially missing limbs Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports Nervous system condition, for example, migraine headaches, Parkinson's disease, multiple sclerosis (MS) Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities Partial or complete paralysis (any cause) Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema Short stature (dwarfism) Traumatic brain injury Disability Status Select... 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