Staff Machine Learning Engineer
Hive
San Francisco, CA · Posted October 15, 2026
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Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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Pay compared with the market
This listing does not state pay. Across 36 open staff machine learning engineer listings that state pay, the middle half runs $230,000 to $280,500 and the median is $270,500.
Listed pay is what employers advertise, not what people are paid.
Staff Machine Learning Engineer salaries by state · Check your own pay
How AI is used in this kind of work
Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
About Deploy
Deploy is an intelligence infrastructure platform that gives developers and enterprises access to open source and proprietary AI models. For leading open source LLMs, Deploy operates an optimized model inference engine that keeps costs and latency low while maintaining high throughput. Deploy also offers a set of proprietary AI models that address challenges in content safety, AI & deepfake detection, sponsorship intelligence, and IP & publicity protection. Trusted by the world's largest and most innovative organizations, Deploy's solutions unlock high-performance AI model inference at production scale.
Deploy has raised more than $200M from leading investors, including Tomales Bay Capital, General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. The company has more than 250 employees across offices in San Francisco, Seattle, New York, and Delhi.
Staff Machine Learning Engineer
In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
Write and maintain scalable, performant code that can be shared across platforms
Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
Improve engineering standards, tooling, and processes
Develop novel, accurate, and performant ML algorithms for use at scale
Conduct metric-driven research experiments to improve model performance
Provide mentorship to and help onboard ML engineers
Lead cross-functional collaboration with other teams
Contribute to defining strategic direction, planning the roadmap
Maintain awareness of industry best practices for data maintenance handling as it relates to your role
Adhere to policies, guidelines and procedures pertaining to the protection of information assets
Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Minimum Requirements
You have a Bachelor's Degree in computer science or a related field
You have 8+ years of experience building web applications
You have successfully implemented highly-available distributed systems/microservices
You have delivered scalable backend APIs
You have strong interpersonal and communication skills with a bias towards action
You have experience writing code and training across distributed systems
You have the ability to understand and make well-reasoned tradeoffs in designing features
You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
You can lead end to end development of new products
Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Deploy, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Deploy and we hope to meet you soon!
The current expected base salary for this position ranges from $200,000 - $300,000. Actual compensation may vary depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.