Jobs in San Francisco, CA (Now Hiring) — 12,843 open at 2,599 companies — Page 412
Ginas Tech Jobs
Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
San Francisco, California, United States · Remote Solely
$170k–$200k/yr
Senior+
Job Description Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolvi…
Skills: Deep Learning, Transformer Architectures, PyTorch, JAX, Distributed Training
Ginas Tech Jobs
Member of Technical Staff, Machine Learning, Artificial Intelligence (AI) Required, Work From Home
San Francisco, California, United States · Remote OK
$160k–$190k/yr
Mid level
Job Description Member of Technical Staff, Machine Learning, Artificial Intelligence (AI) Required, Work From Home As a Member of Technical Staff, Machine Learning, you will build core ML components. The Member of Techni…
San Francisco, California, United States · On-site
$96k–$117k/yr
Senior
Company Description This is a Position-Based Test conducted in accordance with CSC Rule 111A. Specific information regarding this recruitment process is listed below. *This announcement has been amended to reflect change…
San Francisco, California, United States · On-site
$96k–$117k/yr
Senior
Company Description This is a Position-Based Test conducted in accordance with CSC Rule 111A. Specific information regarding this recruitment process is listed below. Application Opening: Tuesday, July 7, 2026Application…
Skills: Custodial Supervision, Facilities Management, Inventory Control, Safety Program Development, Staff Training
Ginas Tech Jobs
Full Stack Engineer, AI Systems, Artificial Intelligence (AI) Required, Work From Home
San Francisco, California, United States · Remote OK
$140k–$190k/yr
Senior
Job Description Full Stack Engineer, AI Systems, Artificial Intelligence (AI) Required, Work From Home We are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into u…
Skills: Full Stack Engineering, Artificial Intelligence, LLM, RAG Systems, System Design
San Francisco, California, United States · On-site
$100k–$140k/yr
Mid levelVisa sponsorship$48M raised
About us Ulysses designs, manufactures, and operates autonomous surface and subsea vehicles for defense, commercial, and scientific missions. Our platform spans Mako (a modular AUV with 60-hour endurance), Leviathan (an …
San Francisco, California, United States · On-site
$180k–$220k/yr
Senior+$887M raised
Via is hiring a Director of Strategy & Operations to lead part of our West Coast portfolio. This is a significant regional P&L leadership role: you will start out by directly managing markets and a team of Field Operatio…
Senior Director, Software Development, Test Automation
San Francisco, California, United States · On-site
$260k–$390k/yr
Senior+$551M raised
Your Impact at LILA The Role We're hiring a Senior Director, Software Development, Test Automation Systems to architect and build Lila's test automation platform and quality engineering practice for our AI-powered scient…
San Francisco, California, United States · On-site
$110k–$120k/yr
Mid level$1.3B raised
AppsFlyer helps brands make good choices for their business and their customers with its advanced measurement, data analytics, deep linking, engagement, fraud protection, data clean room, and privacy-preserving technolog…
Skills: SQL, Programming Languages, Technical Support, Data Analysis, Troubleshooting
San Francisco, California, United States · On-site
$75k–$95k/yr
Mid level$45M raised
Store Manager San Francisco Parachute’s mission is to help you feel at home. It’s what inspires our retail store teams to come together every day to enhance the quality of our customers’ lives at home. Because we believe…
Skills: Retail Management, Team Leadership, Recruiting, Visual Merchandising, P&L Management
About the Role We’re seeking a Strategic Finance Senior Associate to join Chime’s Growth & Marketing Finance team. This role partners closely with cross-functional leaders across Marketing, Growth, Product, and Data to m…
Skills: Financial Modeling, SQL, Looker, Cohort Analysis, ROI Analysis
About the Team The Inventory Management team is responsible for maintaining inventory levels across the fleet and in the distribution center. They handle all sales and margin forecasting and use that information to proje…
San Francisco, California, United States · On-site
$98k–$165k/yr
Mid level$341M raised
Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded acro…
San Francisco, California, United States · On-site
Senior+$1.1B raised
ABOUT QUINCE Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainab…
San Francisco, California, United States · On-site
$67k–$129k/yr
Mid level$35M raised
About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever…
San Francisco, California, United States · On-site
$245k–$330k/yr
Senior+$266M raised
About the job This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, …
ABOUT QUINCE Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainab…
ABOUT QUINCE Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainab…
The world of digital assets is accelerating in speed, magnitude, and complexity, opening the door to new ways for leveraging the blockchain. Fireblocks’ platform and network provide the simplest and most secure way for c…
San Francisco, California, United States · Remote OK
$128k–$168k/yr
Senior$1.0B raised
The world of digital assets is accelerating in speed, magnitude, and complexity, opening the door to new ways for leveraging the blockchain. Fireblocks’ platform and network provide the simplest and most secure way for c…
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$170k–$200k/yr
Full-time
Medical Insurance, Dental, Vision, Savings Plan Options, Paid Time Off
Posted 30d ago
~40 hrs/week
Remote in San Francisco, California, United States
Responsibilities
Architect and build large-scale ML systems covering training, inference, and deployment. Set technical standards for ML infrastructure and optimize GPU performance for production-grade systems.
Requirements
Requires deep expertise in transformer-based architectures and hands-on experience deploying large-scale models. Proficiency in modern ML frameworks and distributed training tools like DeepSpeed or Ray is essential.
Full job description
Job Description
Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands-on, high-impact role focused on depth. This position is 100% Remote.
Principal Machine Learning Engineer Responsibilities:
Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment.
Design reproducible, high-performance training pipelines across GPU infrastructure.
Architect inference systems that balance latency, throughput, cost, and reliability at scale.
Design and maintain data systems for high-quality synthetic and real-world training data.
Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
Work under real production constraints: latency, cost, reliability, and safety
Principal Machine Learning Engineer Outcomes:
ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets.
Models deployed to production achieve measurable quality improvements and meet user-impact goals.
Production issues are proactively monitored, debugged, and resolved with clear root-cause analysis.
Team and cross-functional collaborators benefit from clear guidance, best practices, and scalable ML solutions.
Research-to-production cycles are efficient, safe, and continuously improve the product experience.
Qualifications
Principal Machine Learning Engineer Qualifications:
Strong background in deep learning and transformer-based architectures.
Artificial Intelligence (AI) experience required.
Hands-on experience training, fine-tuning, or deploying large-scale ML models in production.
Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly.
Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray).
Strong software engineering fundamentals; you write robust, maintainable, production-grade systems.
Experience with GPU optimization, including memory efficiency, quantization, and mixed precision.
Comfort owning ambiguous, zero-to-one ML systems end-to-end.
A bias toward shipping, learning fast, and improving systems through iteration.
Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer.
Contributions to open-source ML or systems libraries.
Background in scientific computing, compilers, or GPU kernels.
Experience with RLHF pipelines (PPO, DPO, ORPO).
Experience training or deploying multimodal or diffusion models.
Experience with large-scale data processing (Apache Arrow, Spark, Ray).
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
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