Senior ML Engineer, Agentic AI

Ellipsis Health, Inc.; San Francisco (CA); Hybrid; USD 160,000 - 210,000; Full time

Benefits offered by this job

401(k) matching

Health insurance

Vision insurance

Dental insurance

Flexible paid time off

Job summary

Ellipsis Health, Inc. is seeking a Senior ML Engineer to contribute to AI Research & Engineering. This hybrid role focuses on designing and building scalable AI systems while ensuring collaboration with clinical and product teams.

Candidates should have significant experience in software development and strong proficiency in Python and machine learning technologies. The salary range for this position is between $160,000 to $210,000 based on qualifications and experience.

Qualifications

• 5+ years of software development experience focusing on product design and architecture.
• Experience deploying LLM-powered applications in production environments.
• Advanced proficiency in distributed machine learning frameworks.

Responsibilities

• Lead the technical vision for the Agentic AI roadmap.
• Design scalable systems for AI applications.
• Bridge the gap between ML research and enterprise design.
• Evaluate and maintain quantitative evaluation frameworks.
• Collaborate with clinical experts and engineers.

Skills

Python programming

Machine Learning frameworks (PyTorch, JAX, TensorFlow)

Product design

Software development

Education

Bachelor’s degree in Computer Science or equivalent

Job description

Senior ML Engineer, Agentic AI

Employment Type

Full time

Location Type

Hybrid

Compensation

• $160K – $210K

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.

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.