Machine Learning Engineer Jobs in San Francisco, USA

Looking for a machine learning engineer job in San Francisco? Choose from 96 open roles at 39 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.

96 Open roles
39 Companies hiring
328K Average salary

What do Machine learning engineers in San Francisco work on?

The roles on this page cover a wide spectrum of ML work. At one end, postings like the Machine Learning Engineer at Latent AI focus on owning end-to-end production systems โ€” training and fine-tuning large language models, building evaluation frameworks, and managing accuracy-latency-cost tradeoffs for clinical workflows. Responsibility for safety and fairness appears repeatedly: the Pinterest Responsible AI posting centres on identifying and mitigating bias across generative AI and recommender systems, while the Anthropic Safeguards ML Infra role sits closer to infrastructure, owning deployment pipelines for safety classifiers and on-call production operations. Recommendation systems and monetisation engineering feature prominently across multiple titles from Pinterest and Airbnb. The Airbnb Trust role combines fraud detection with LLM and agent work. Further along the spectrum, the Pinterest senior manager posting involves leading teams, translating research into production, and mentoring. The Swayable role is narrower, focusing on scientific computing and analytics rather than deep learning infrastructure.

Skills and experience employers ask for

Python and LLMs are the most widely mentioned skills across these postings, followed closely by PyTorch. PhD and Master's degree appear in roughly half the postings each, though these are mentions in job descriptions rather than stated requirements, and the small sample means the proportions should not be treated as definitive market signals. Publications, reinforcement learning, and agent-based work appear in a meaningful minority. TensorFlow is mentioned noticeably less often than PyTorch.

Python 61%
LLMs 60%
PyTorch 55%
Evaluation 52%
PhD 45%
Master's degree 40%
Reinforcement learning 29%
TensorFlow 28%
Agents 28%
Fine-tuning 28%
Publications 27%
A/B testing 25%
SQL 20%
Transformers 20%

Machine Learning Engineer roles that state a salary

The employers' own advertised ranges, for individual roles at different levels โ€” not an average and not a market rate.

San Francisco office, hybrid or remote?

Most postings in this set are listed as onsite, with a smaller portion hybrid. A minority allow remote work. Work-mode is stated for all postings on this page, so there are no unknowns in the counts. The Pinterest senior manager role is an example of an exception within what is otherwise a predominantly office-based set: its summary notes that the position can be located anywhere in the US with in-office visits one to two times per quarter. Candidates should confirm current arrangements directly with each employer, as stated modes can change.

Make your application specific to the work

  1. Review the seniority match Most postings on this page sit at senior, staff, or lead level, with a very small proportion at junior or manager grade. Check the seniority band and stated years-of-experience threshold before applying, as these vary considerably even within the same employer.
  2. Read the skills section carefully Postings here range from scientific Python and classical ML through to LLM fine-tuning, reinforcement learning, and production ML infrastructure; confirm which technical stack and domain each role emphasises before tailoring your application materials.
  3. Check degree and publications expectations PhD and Master's degree are mentioned in a large share of descriptions, and publications appear in roughly a quarter; note that the fact pack records these as mentions rather than confirmed hard requirements, so read each posting's own language directly.
  4. Apply through each employer directly Use the job links on this page to reach the original postings, where you can verify current status, salary ranges if disclosed, and any visa or sponsorship information โ€” none of which should be assumed from the employer's general reputation.

Questions about Machine Learning Engineer jobs in San Francisco

The named employers in these postings include Waymo, Pinterest, OpenAI, Anthropic, Lyft, Together AI, Airbnb, Adobe, Swayable, Latent AI, and Perplexity, among others listed in the full set.

Only a minority of postings on this page include advertised pay. The ranges that are stated come from OpenAI and Perplexity; they vary widely by role and level, with some OpenAI postings showing base ranges starting around 220,000 USD and reaching up to 555,000 USD for an engineering manager position. These are individual posted ranges, not representative of all roles on this page.

PhD is mentioned in roughly half the postings in this set. However, skills counts reflect mentions in job descriptions, not confirmed hard requirements. You should read the specific language in each posting to understand whether it is required or preferred.

A minority of the postings are listed as remote, and a smaller but meaningful portion are listed as hybrid. The majority are onsite. One sample summary, the Pinterest senior manager role, explicitly describes a distributed arrangement with quarterly in-office visits. All postings on this page have a stated work mode.

Most postings in this set are at senior, staff, or lead level. A small number are at manager or director grade, and only one is listed as junior. For many postings the seniority is not stated explicitly in the title. Individual postings typically specify years of experience, ranging from five years at the lower end to eight or more for staff and infrastructure roles.

Jobs checked 2 hours ago. ยท Guide reviewed 14 September 2026.