Staff Machine Learning Engineer
San Francisco
- Pay
$200,000–300,000/year · BaseAnnual period assumed · Location-specific pay — pay source
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. Employment type
Read the full posting- Work setting
On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
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 throughout. 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.
Read the full posting
What you’ll work on
Full postingTake ML models from design and training through deployment and ongoing tuning
Write and maintain scalable, performant code shared across platforms
Develop novel, accurate ML algorithms for use at scale
Run metric-driven research experiments to improve model performance
Mentor and onboard ML engineers
From the employer’s posting
Everything involved in applying a ML model to a production use case
Write and maintain scalable, performant code that can be shared across platforms
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
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in computer science or a related field
- 8+ years building web applications
- Experience with highly available distributed systems or microservices
- Expert in ML frameworks such as PyTorch or TensorFlow
- Expert in Python and/or shell scripting
Qualification wording
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 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
Education & alternatives
Minimum Requirements - You have a Bachelor's Degree in computer science or a related field - You have 8+ years of experience building web applications
Tools in this posting
- Python
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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 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
About Hive
Deploy is an intelligence infrastructure platform that gives developers and enterprises access to open source and proprietary AI models.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 2026 · 3 days ago
- Recorded sightings
- 10
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Oct 15, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
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 throughout. 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.
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.
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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. Employment type
- Location & working pattern
San Francisco
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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 throughout. 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
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