Staff AI Engineer – Clinical AI

AI EngineerMachine Learning EngineerFull TimeRemoteTeam 201-500Since 1993H1B No SponsorCompany SiteLinkedIn

Location

Illinois + 1 moreAll locations: Illinois, Texas

Posted

12 days ago

Salary

$170K - $250K / year

Bachelor Degree8 yrs expEnglishAWSAzureCloudDockerElastic SearchJavaKubernetesPython

Job Description

• Own the full ML lifecycle, including data ingestion, training, validation, deployment, monitoring, retraining, and retirement. • Transition AI/ML prototypes into scalable, production-ready systems with CI/CD pipelines, automation, and observability. • Lead system design and architecture discussions, providing guidance on ML systems, MLOps, and AI infrastructure. • Develop and maintain AI-driven applications and inference services, optimizing for performance, scalability, reliability, and cost. • Integrate LLMs, generative AI, and NLP solutions into IMO Health products, focusing on unstructured clinical data. • Implement monitoring, alerting, logging, and dashboards to ensure model quality, detect drift, and maintain operational SLAs. • Build, maintain, and optimize CI/CD pipelines, automation scripts, and Infrastructure-as-Code for production ML systems. • Apply containerization (Docker, Kubernetes) and cloud infrastructure best practices to manage production environments. • Mentor and guide engineers, enforce technical standards, and drive reduction of technical debt. • Conduct root cause analysis of production defects and implement durable fixes. • Advocate for non-functional requirements (availability, scalability, reliability, maintainability) and design systems accordingly. • Collaborate cross-functionally with Product, Data Science, Architecture, and Engineering teams to align AI solutions with business goals.

Job Requirements

  • 8+ years of professional experience in software engineering, AI/ML engineering, or related roles, building and operating production-grade systems.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience).
  • Strong foundation in computer science fundamentals (data structures, algorithms, design patterns, operating systems, networking).
  • Expert-level coding skills in Python or Java, with a strong emphasis on production-quality software engineering practices.
  • Hands-on experience owning ML systems in production, including deployment, monitoring, retraining, and optimization.
  • Experience designing and operating CI/CD pipelines, automation, and observability for ML systems.
  • Deep experience with cloud platforms (AWS or Azure), containerization, and Infrastructure-as-Code.
  • Experience with MLOps tools and workflows (e.g., MLflow, SageMaker, Kubeflow).
  • Experience integrating and deploying LLMs, generative AI, and agentic systems in production environments.
  • Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling); healthcare exposure is a plus.
  • Experience with Elasticsearch and vector databases for embedding-based search and retrieval.
  • Proven ability to translate business needs into scalable, reliable technical solutions, balancing technical debt and delivery velocity.
  • Strong system design skills for high-performance, distributed, and scalable systems.
  • Excellent communication and collaboration skills across cross-functional, distributed teams.
  • Self-starter who can operate autonomously and own complex systems end to end.

Benefits

  • Comprehensive benefits package

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