Network administrator jobs in Novato, CA - 876 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 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

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

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

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

Ready to play a key role in building the future of living? Join Samara in tackling California's housing shortage and enabling people to attain sustainable housing without compromising design or quality. Our flagship product, Backyard, is a fully turnkey, premium accessory dwelling unit (ADU) designed for homeowners and real estate developers. As we expand our offerings and scale our in-house development initiatives, we're at a pivotal moment, redefining homeownership through high-quality, attainable infill housing. Backed by top-tier investors, including Airbnb, Thrive Capital, and 8VC, Samara is positioned for significant growth and market impact. To support our next phase of growth, we're hiring product-focused engineers to advance and scale the technical foundation of our modular system. These roles go beyond traditional design work-they refine system standards, improve factory repeatability, and ensure our units are code-compliant, manufacturable, and built to the highest standards of quality and performance. The MEP Systems Engineer will be responsible for the detailed design and implementation of mechanical, electrical, plumbing, and PV systems tailored for modular construction building systems. This role requires a deep understanding of MEP systems combined with practical experience in modular construction. You will collaborate closely with leadership, crossfunctional design and engineering teams to integrate all technical and user experience requirements into our designs to ensure optimal functionality, sustainability, and compliance with all regulations. What You'll Do Design and develop integrated MEP systems for our new and existing designs including solar energy systems, including PV and ESS, optimized for prefabricated modular construction Ensure that solar and energy storage designs align with overall MEP system functionality and building energy requirements Lead the creation of comprehensive design documents, schematics, component material selections and system layouts, preferably using CAD and BIM software Provide technical leadership during the installation and commissioning phases to ensure systems meet design specifications and performance standards Conduct system testing and validation to ensure functionality, efficiency, and safety of both MEP and PV installations Collaborate closely with installation teams to facilitate seamless and efficient factory and onsite implementation of design Engage in research and application of the latest technologies and practices in renewable energy and modular construction Work with program managers and other engineering disciplines to ensure holistic integration of all systems within Samara modular units What We're Looking For Modular construction experience in factory builds, multi-mod, stackable and/or other hands on related experience. Licensed Electrician or Mechanical Contractor -and/or- Bachelor's degree in Mechanical, Electrical, or Energy Systems Engineering, or a related field Professional Engineering (PE) license preferred Minimum of 7 years of experience in one of the following: Mechanical, Electrical, Solar and/or Plumbing System design Comprehensive knowledge of building codes, safety regulations, and sustainability practices relevant to MEP and renewable energy systems Proficiency in design software such as Onshape, Revit, and/or other BIM methodologies preferred Excellent problem-solving skills and the ability to adapt designs to changing technological and regulatory landscapes Strong communication and leadership skills, capable of driving project decisions and managing complex stakeholder relationships Ability to travel to our factory in Mexico up to 25-40%. What We Offer Salary range of $120-160K and performance-based bonuses. Hybrid work schedule with 3 days each week in our Redwood City office. Snacks and Lunch on in-office days Early stage employee equity. Exceptional health, dental, and vision insurance. 401k eligibility after 6 months. Flexible PTO policy. How to Apply If you're excited to support Samara's mission and have the skills to match, we'd love to hear from you. Please submit your resume and a brief letter of introduction to our team. Let's build something extraordinary-together.

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

About 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 Reinforcement Learning Engineering 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 4+ 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: High performance, large scale distributed systems Large scale LLM training 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: Annual Salary:$315,000-$425,000 USDLogistics 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. #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 tech-focused organization is looking for a Forward Deployed Engineer to lead complex AI deployments with government clients. You will be responsible for managing technical delivery, embedding within client teams, and utilizing advanced AI technologies to solve critical challenges. Ideal candidates will have 5+ years of experience in engineering, a TS/SCI clearance, and a strong ability to communicate effectively while navigating fast-paced environments. This position allows for hybrid work with significant travel requirements. #J-18808-Ljbffr

Cupertino, California, United States Machine Learning and AI The Siri organization is looking for passionate Machine Learning Systems Engineers to join us in developing and shipping state-of-the-art generative AI technology to advance Siri and Apple Intelligence for Apple's customers. Siri is being elevated by the huge opportunities that AI brings.The organization is responsible for training on-device & cloud models, evaluating various approaches, pushing the envelope with the latest generative AI research developments, and ultimately delivering product critical models that power Siri and Apple Intelligence experiences. These models ship across a wide range of products at Apple, including iPhone, Mac, Apple Watch and more, enabling millions of people around the world to get things done every day. Our team provides an opportunity to be part of an incredible research and engineering organization at Apple. By joining the team, you will work with highly talented machine learning researchers and engineers, and work on meaningful, challenging and novel problems. Description As a Machine Learning Systems Engineer, you will work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference. You will be working across the ML stack at Apple, finding opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon. You will be joining a team that spans data, modeling, evaluation, deployment and working with engineers across ML infrastructure, inference, and framework teams. You will write production-level code to train and deploy models that will impact Apple's customers and enrich their lives. You are an ideal candidate if you: Are not afraid of CUDA OOM or NCCL errors Can dig deep into an ML library to understand how tiny details impact the model Can understand complex ML systems that include data, training pipeline, export, and inference engine Minimum Qualifications Experience in model lifecycle of training, evaluation, and deployment of models Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers, CNN) and ML training loop Strong proficiency in Python and ML framework such as PyTorch Bachelor's degree in Computer Science, Engineering, or related discipline, or equivalent industry/project experience Preferred Qualifications Collaborative with experience working in large inter-teams projects Expertise in ML and LLM optimization such as quantization, KV Cache, Speculative Decoding Familiarity with ML training methodologies such as FSDP, DDP, and other parallelism Experience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM. Experience in optimizing LLM models and deploying LLM models Proficiency in a compiled programming language (e.g. Swift, C/C++, Java) At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . #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

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

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

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 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