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Staff/Senior Machine Learning Engineer, Clinical AI

United States, Boston - Massachusetts

SpringCube

Full-time - Senior Engineer

Healthcare Services & Tech

Posted 4 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading healthcare technology company is advancing precision medicine through AI-driven clinical solutions. Their proprietary platform integrates real-world evidence to provide actionable insights for physicians, enabling more informed treatment decisions and improved patient outcomes. The organization focuses on deploying advanced AI models at scale to enhance clinical workflows, accelerate research, and transform healthcare delivery.

Summary
The Staff/Senior Machine Learning Engineer will design, build, and maintain production AI pipelines and infrastructure for clinical applications, leveraging natural language processing and large language models (LLMs) at scale. This role will support clinical workflow optimization, trial matching, and medical research through innovative AI solutions.

Responsibilities

  • Build and operate production AI pipelines, including LLM-powered extraction, batch orchestration, and inference, ensuring reliability, cost-efficiency, and low latency
  • Design and maintain Airflow-based orchestration for batch clinical workflows
  • Implement observability systems (metrics, logging, alerting) to detect regressions proactively
  • Develop evaluation infrastructure to continuously measure clinical model output quality, including regression detection, drift management, dashboards, and gold-set management
  • Ship platform tooling and SDKs to accelerate ML Scientists and downstream users
  • Partner with ML Scientists to debug model output issues and identify root causes (data, prompt, pipeline)
  • Participate in on-call rotation for production systems
  • Collaborate with platform and infrastructure teams to optimize cloud services (GCP) for performance, security, and cost
  • Author and review design documents for cross-team projects
  • Raise the engineering bar through code and design reviews

Required Qualifications

  • Strong production experience with Python
  • Experience designing, building, and integrating microservices in production
  • Hands-on experience deploying data orchestration workflows (Airflow or equivalent)
  • Familiarity with cloud-native services (GCP preferred)
  • Built monitoring, observability, and alerting systems for production environments
  • Experience with at least one major ML framework (LangGraph, PyTorch, spaCy, or equivalents)
  • Strong written and verbal communication; experience authoring and reviewing RFCs, PRDs, or equivalent
  • Collaborative mindset with research scientists, PMs, and clinicians

Preferred Qualifications

  • Hands-on experience operating production systems, including on-call rotations and incident response
  • Experience building evaluation or quality measurement systems for ML or LLM outputs
  • Practical experience with production LLM applications (prompt engineering, agents, RAG, extraction pipelines, LLM evaluations)
  • Built internal platforms or SDKs supporting other engineers or scientists
  • Experience with clinical or biomedical data (EHR, genomics, pathology, clinical notes)
  • Contributions to relevant open-source projects

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.

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