Machine Learning Manager
San Francisco
- Pay
$180,000–250,000/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 $180,000 - $250,000. 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 postingLead and mentor a team of machine learning engineers
Build the team's roadmap with product, engineering, devops, labeling and sales
Drive delivery of model milestones with tested features and quality metrics
Take part in the full cycle from data collection through production deployment
Contribute to product technical design and architecture
From the employer’s posting
Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
Participate in products technical design and architecture
What you’ll bring
All qualificationsCore experience
- 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
- 2+ years experience managing machine learning teams
Qualification wording
4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
2+ years experience managing machine learning teams
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.
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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.
Machine Learning Manager
In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We’re interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
- Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
- Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
- Participate in products technical design and architecture
- Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
- Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
- Implement and manage security protocols such as training, code review, and best practices
- Own and manage the risk and security of your business function in coordination with the Security Team
- 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
Requirements
- Undergraduate or graduate degree in computer science or similar technical field
- 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
- Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
- 2+ years experience managing machine learning teams
- You have an ability to understand and make well-reasoned tradeoffs in designing features
- Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
- Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
- Have experience collaborating with product managers and labeling team in delivering model improvements
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 $180,000 - $250,000. 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 $180,000 - $250,000. 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. Machine Learning Manager
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