AI / Machine Learning Talent

AI Lab - AI/ML Opportunities

Location: San Jose, CA (Hybrid – Onsite 3x per week on Tues, Wed, Thurs)

About Ensemble’s AI Lab

Ensemble Health Partners is the leading Revenue Cycle Management (RCM) partner to U.S. health systems. We sit between hospitals, payers, and patients, and we are responsible for billions of dollars of healthcare revenue moving accurately and on time. AI is increasingly central to how we do that work — from predicting denials and automating coding to flagging payment integrity issues and routing accounts to the right action at the right time. These roles exists where those AI systems meet the business outcomes we are paid to deliver.

We are continuously building a pipeline of exceptional AI/ML talent across research, data science, and engineering. This general application allows candidates to be considered for multiple roles across the AI Lab. Final role alignment (e.g., Data Scientist, AI Research Scientist, Machine Learning Engineer) and leveling will be determined based on interview performance, experience, and team needs.

What You’ll Work On

Depending on your background and strengths, you may:

• Design, build, evaluate, and improve machine learning and AI systems in production environments

• Translate business problems into AI/ML solutions and measurable outcomes

• Develop and run experiments to evaluate models, including defining metrics, datasets, and success criteria

• Productize models into scalable, reliable, and cost-efficient services

• Optimize training and inference performance (latency, throughput, cost)

• Analyze real-world system behavior and production data to drive continuous improvements

• Partner cross-functionally with engineering, product, and domain experts to deliver end-to-end solutions

• Contribute to AI research, experimentation, and adoption of new techniques where applicable

• Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical stakeholders

What We’re Looking For

We are hiring across a range of profiles, but strong candidates will demonstrate:

• Proven experience working with machine learning or AI systems in real-world or production settings

• Strong problem-solving skills and ability to operate in ambiguous, evolving environments

• Ability to connect technical work to measurable business or product outcomes

• Experience collaborating across teams (engineering, product, data, or research)

• Ownership mindset—taking work from idea through execution and impact

Technical Skills (vary by role)

Candidates may have experience with some combination of:

• Programming: Python (required), plus familiarity with SQL and other languages (e.g., Java, C++, Go)

• Machine Learning: Model development, evaluation, and optimization

• Deep Learning: Frameworks such as PyTorch, TensorFlow, Hugging Face

• LLMs & Modern AI: Fine-tuning, prompt engineering, evaluation frameworks, or emerging techniques (e.g., PEFT, RLHF)

• Data & Analytics: Statistics, experimentation, causal inference, and working with real-world datasets

• Systems & Infrastructure (Engineer-leaning candidates):

  • Model serving, APIs, and distributed systems

  • Training at scale (e.g., multi-GPU / distributed training)

  • Performance optimization and cost efficiency

• Research (Research-leaning candidates):

  • Experiment design, evaluation rigor

  • Reading and applying state-of-the-art research

  • Publication or novel contributions (preferred, not required)

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or related field required

• Master’s or PhD preferred for certain roles (especially research-oriented positions), but not required for all paths

• Relevant industry experience typically ranges from 3+ years (Senior) to advanced leadership/ownership experience (Staff/Principal)

The base salary range for these roles is $154,100 to $341,600.