Monitor model performance in production, identify issues, propose remediation steps, and ensure strong test coverage and system reliability.
Utilize contemporary software engineering practices to implement scalable, secure, and maintainable AI/ML systems.
Develop and customize API integrations to enable seamless connectivity between cloud‑based systems and ML services.
Participate in architectural discussions to ensure ML platforms meet compliance, performance, and scalability standards.
What You’ll Need
Bachelor’s degree in Computer Science, Data Analytics, Software/Computer Engineering, Computational Statistics, Mathematics, or a related discipline.
3+ years of end‑to‑end ML development in production (data prep, feature engineering, modeling, calibration, deployment, monitoring, maintenance).
3+ years of MLOps experience building production pipelines (CI/CD, model registry, feature store), implementing monitoring & drift detection, and automating retraining.
3+ years of Python for production ML (testing, packaging, type hints, linting) and SQL for analytical and production workloads; Scala a plus.
2+ years working with distributed compute and cloud ML environments (e.g., Spark/Databricks on Azure/AWS/GCP) and modern data ecosystems (data lakes, DBMS).
Strong debugging and optimization skills across data and ML workflows.
Track record of ownership and problem solving—driving measurable impact and quality under ambiguity and evolving requirements.
Ability to communicate technical decisions clearly and contribute to documentation and design discussions.
Demonstrated system design & architecture skills for scalable, high‑performance ML services and batch/streaming workflows; familiarity with API design and service integration patterns.
Proven understanding of tradeoffs in latency, cost, performance, and compliance.
Preferred
1+ years of Databricks experience + some experience in infrastructure/networking
1+ years implementing LLM‑based solutions in production (prompt/response design, evaluation frameworks, guardrails/safety, latency/cost optimization).
1+ years designing compliant ML platforms (e.g., HIPAA, SOC 2) and working with PHI/PII governance, access controls, and auditability.
Our mission is to reinvent healthcare to help patients live their best lives, and we proudly live our mission-driven values:
We care deeply about the people we serve.
We are better when we work together.
Humility is a source of our strength.
We bring joy to our work.
We deliver on our promises.
We are committed to diversity, equity, and inclusion throughout our recruiting practices. Everyone is welcome and included. We value our differences and learn from each other. Our team members come in all shapes, colors, and sizes. No matter how you identify your lifestyle, creed, or fandom, we value everyone's unique journey.
Oh, and one more thing … a recent study shows that men apply for a job or promotion when they meet only 60% of the qualifications, but women and other marginalized groups apply only if they meet 100% of them. So, if you think you’d be a great fit, but don’t necessarily meet every single requirement on one of our job openings, please still apply. We’d love to consider your application!
Come join us and help our patients live their best lives. Learn more at www.interwellhealth.com.
It has come to our attention that some individuals or organizations are reaching out to job seekers and posing as potential employers presenting enticing employment offers. We want to emphasize that these offers are not associated with our company and may be fraudulent in nature. Please note that our organization will not extend a job offer without prior communication with our recruiting team, hiring managers and a formal interview process.
