Pay
In line with similar jobs
$160K–$210K against $166K–$240K, the middle half of what similar US postings state.
From 1,319 postings in the last year. Stated ranges, not salaries paid.
Senior ML Engineer, Agentic AI
San Francisco - Hybrid · San Francisco, California, United States
Live, first seen by us today- Pay
USD 160,000–210,000/yearAnnual period assumed — pay source
We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off. The typical salary range for this role is $160,000 to $210,000 USD, depending on skills, qualifications, and relevant experience. Background Checks:
Read the full posting- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
R&D › Engineering — team source
Department: R&D › Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status (e.g., H-1B, TN, etc.)?
From the employer’s application form
What you’ll work on
Full postingResearch-to-Production Translation: Bridge the gap between frontier machine learning research and enterprise software design.
Implement and adapt state-of-the-art techniques in post-training fine-tuning, preference alignment, and automated prompt optimization.
Implement state-of-the-art LLM-as-a-judge rubrics, and statistical tracking to evaluate agent capabilities and guarantee zero-regression product updates.
From the employer’s posting
Advanced Agentic Architecture: Design, build, and optimize scalable systems and orchestration pipelines capable of deep multi-step reasoning, dynamic memory allocation, long-context evaluation, and high-fidelity tool utilization. Research-to-Production Translation: Bridge the gap between frontier machine learning research and enterprise software design. Implement and adapt state-of-the-art techniques in post-training fine-tuning, preference alignment, and automated prompt optimization. Rigorous Evaluation & Benchmarking: Architect and maintain multi-dimensional quantitative evaluation frameworks and continuous testing infrastructure. Implement state-of-the-art LLM-as-a-judge rubrics, and statistical tracking to evaluate agent capabilities and guarantee zero-regression product updates.
Research-to-Production Translation: Bridge the gap between frontier machine learning research and enterprise software design. Implement and adapt state-of-the-art techniques in post-training fine-tuning, preference alignment, and automated prompt optimization. Rigorous Evaluation & Benchmarking: Architect and maintain multi-dimensional quantitative evaluation frameworks and continuous testing infrastructure. Implement state-of-the-art LLM-as-a-judge rubrics, and statistical tracking to evaluate agent capabilities and guarantee zero-regression product updates. Data Mix Optimization: Develop and scale automated data curation pipelines to extract, filter, and structure user feedback signals, execution logs, and expert labels into ultra-high-quality training datasets for model fine-tuning.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience.
- 5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role).
Preferred experience
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative technical field.
- 8+ years of industry experience specializing in advanced data structures, algorithms, distributed systems, and heavy-duty scalable ML infrastructure.
- 3+ years of technical leadership experience, including leading complex technical project workstreams, defining organizational engineering directions, or directly mentoring technical talent.
- Experience working within complex, highly collaborative matrixed organizations on high-acuity, deeply regulated technical integrations (e.g., healthcare, fintech, or aerospace).
Qualification wording
Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience.
5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role).
Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative technical field.
8+ years of industry experience specializing in advanced data structures, algorithms, distributed systems, and heavy-duty scalable ML infrastructure.
3+ years of technical leadership experience, including leading complex technical project workstreams, defining organizational engineering directions, or directly mentoring technical talent.
Experience working within complex, highly collaborative matrixed organizations on high-acuity, deeply regulated technical integrations (e.g., healthcare, fintech, or aerospace).
Education & alternatives
Minimum Qualifications - Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience. - 5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role).
- Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience. - 5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role). - Advanced programming proficiency in Python and deep hands-on expertise with distributed machine learning or deep learning frameworks (e.g., PyTorch, JAX, or TensorFlow).
Preferred Qualifications - Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative technical field. - 8+ years of industry experience specializing in advanced data structures, algorithms, distributed systems, and heavy-duty scalable ML infrastructure.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Nov 6, 2026today
- Recorded sightings
- 1
- Reposted
- once since Aug 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 6 and day 70.
From 4,599 similar postings that came down. Coming down is not always a hire.
Ellipsis Health is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- 50% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- PyTorch
- TensorFlow
Where the posting names them
- 5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role). - Advanced programming proficiency in Python and deep hands-on expertise with distributed machine learning or deep learning frameworks (e.g., PyTorch, JAX, or TensorFlow). - Proven track record of architecting, implementing, and deploying complex LLM-powered applications, multi-agent orchestrations, or autonomous systems in a production environment.
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
Has Ellipsis Health posted this job before?
Yes. We’ve followed one other Senior ML Engineer, Agentic AI job there since August 2026. It came down after 75 days.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Ellipsis Health is creating cutting-edge AI/ML products that solve healthcare staffing challenges and administrative burdens using conversational AI and our patented voice biomarker technology—helping deliver better healthcare for everyone. We are headquartered in Silicon Valley and are funded and supported by some of the most preeminent venture capital teams.
In this role, you will be a core contributor and technical leader within our AI Research & Engineering team. Operating at the sweet spot between cutting-edge scientific research and production-grade systems, you will drive the conceptualization, architecture, and deployment of frontier agentic systems. You will collaborate directly with core infrastructure and platform teams to translate algorithmic breakthroughs in LLMs and agentic AI into robust, secure, and low-latency clinical applications.
Responsibilities:
Technical Leadership & Vision: Act as the technical authority for the Agentic AI roadmap, steering engineering pods from initial research prototyping through to production scale.
Advanced Agentic Architecture: Design, build, and optimize scalable systems and orchestration pipelines capable of deep multi-step reasoning, dynamic memory allocation, long-context evaluation, and high-fidelity tool utilization.
Research-to-Production Translation: Bridge the gap between frontier machine learning research and enterprise software design. Implement and adapt state-of-the-art techniques in post-training fine-tuning, preference alignment, and automated prompt optimization.
Rigorous Evaluation & Benchmarking: Architect and maintain multi-dimensional quantitative evaluation frameworks and continuous testing infrastructure. Implement state-of-the-art LLM-as-a-judge rubrics, and statistical tracking to evaluate agent capabilities and guarantee zero-regression product updates.
Data Mix Optimization: Develop and scale automated data curation pipelines to extract, filter, and structure user feedback signals, execution logs, and expert labels into ultra-high-quality training datasets for model fine-tuning.
Cross-Functional & Clinical Collaboration: Work closely within a highly matrixed, collaborative organization alongside clinical experts, product managers, and software engineers to ensure AI platforms operate safely and ground outputs in validated healthcare protocols.
Mentorship & Engineering Excellence: Foster a culture of technical rigor by setting high coding standards, leading design reviews, standardizing tooling, and mentoring other ML and software engineers across the team.
Minimum Qualifications
Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience.
5+ years of practical software development experience with a heavy emphasis on product design, core system architecture, and shipping scalable software platforms (or 2+ years of post-PhD industry experience in a dedicated AI research/engineering role).
Advanced programming proficiency in Python and deep hands-on expertise with distributed machine learning or deep learning frameworks (e.g., PyTorch, JAX, or TensorFlow).
Proven track record of architecting, implementing, and deploying complex LLM-powered applications, multi-agent orchestrations, or autonomous systems in a production environment.
Preferred Qualifications
Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative technical field.
8+ years of industry experience specializing in advanced data structures, algorithms, distributed systems, and heavy-duty scalable ML infrastructure.
3+ years of technical leadership experience, including leading complex technical project workstreams, defining organizational engineering directions, or directly mentoring technical talent.
Experience working within complex, highly collaborative matrixed organizations on high-acuity, deeply regulated technical integrations (e.g., healthcare, fintech, or aerospace).
Research Excellence: A solid track record of contributions or publications at top-tier machine learning venues (e.g., NeurIPS, ICML, KDD) with a specific focus on agentic frameworks, reinforcement learning, or data benchmark.
Salary and Benefits:
We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off.
The typical salary range for this role is $160,000 to $210,000 USD, depending on skills, qualifications, and relevant experience.
Background Checks:
As a health technology company, we reserve the right to run background checks on candidates to whom we extend offers, in compliance with applicable laws. We evaluate candidates holistically and comply with all “ban the box” regulations.
Assistance:
If you have a disability or require accommodations during the application or recruitment process, please contact careers@ellipsishealth.com.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off. The typical salary range for this role is $160,000 to $210,000 USD, depending on skills, qualifications, and relevant experience. Background Checks:
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.