ML Engineer
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Before you apply
SalaryNo pay range posted
LocationSan Francisco
Work modehybrid
Typefull-time
DepartmentEngineering
Company size5+ people
PostedOct 30, 2026 · 5d ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Strong software engineering fundamentals and experience building production systems
Hands-on experience developing and deploying machine learning solutions
Proficiency in Python
Familiarity with modern ML frameworks and tooling
Experience evaluating model performance and improving systems through experimentation
Understanding of ML infrastructure, deployment, monitoring, and production reliability
Ability to work independently, communicate clearly, and collaborate across disciplines
Comfort operating in a fast-moving environment with evolving technical and product requirements
Experience with large language models, generative AI, or speech-related ML systems
Experience with model evaluation, fine-tuning, or inference optimization
Familiarity with healthcare technology or other high-reliability product environments
Experience building ML products in an early-stage startup
Skills
Python
ML frameworks
LLMs
generative AI
speech-related ML
Machine Learning Engineer
Location: San Francisco, CA
Team: Engineering
Employment Type: Full-time
About Freed
Freed is building AI-powered tools that reduce the administrative burden on healthcare professionals, giving clinicians more time to focus on patient care.
About the role
We’re looking for a Machine Learning Engineer to help develop, improve, and scale the AI systems powering our products.
About the Role
As a Machine Learning Engineer at Freed, you’ll work at the intersection of applied machine learning, software engineering, and product development.
You’ll help take ML solutions from experimentation into production, working closely with engineers and cross-functional partners to build reliable, high-quality AI experiences for clinicians.
This role is ideal for someone who enjoys solving complex technical problems, moving quickly, and seeing their work make a tangible impact.
What You’ll Do
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Develop, evaluate, and improve machine learning models and AI-powered product capabilities.
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Build and maintain production ML pipelines, services, and supporting infrastructure.
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Design experiments and evaluation frameworks to measure model quality, reliability, and performance.
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Collaborate with product and engineering teams to translate user needs into practical technical solutions.
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Improve the scalability, efficiency, and reliability of ML systems in production.
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Investigate model failures, identify opportunities for improvement, and iterate using real-world feedback.
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Contribute to technical decisions and engineering best practices across the ML lifecycle.
What We’re Looking For
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Strong software engineering fundamentals and experience building production systems.
•
Hands-on experience developing and deploying machine learning solutions.
•
Proficiency in Python and familiarity with modern ML frameworks and tooling.
•
Experience evaluating model performance and improving systems through experimentation.
•
Understanding of ML infrastructure, deployment, monitoring, and production reliability.
•
Ability to work independently, communicate clearly, and collaborate across disciplines.
•
Comfort operating in a fast-moving environment with evolving technical and product requirements.
Nice to Have
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Experience with large language models, generative AI, or speech-related ML systems.
•
Experience with model evaluation, fine-tuning, or inference optimization.
•
Familiarity with healthcare technology or other high-reliability product environments.
•
Experience building ML products in an early-stage startup.
Why Freed?
At Freed, you’ll work on meaningful technical challenges with a direct connection to the people using what you build.
You’ll have the opportunity to take ownership, influence technical direction, and help shape AI products that make clinicians’ lives easier.