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Senior AI/ML Operations Engineer

6 hours, 9 minutes ago
United States
Full-time
Senior
AI (Artificial Intelligence)
Software Development
CI/CD Databricks Feature Engineering Generative AI MLflow MLOps Neural Networks Python Random Forest Snowflake SQL XGBoost
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Abacus Insights

Abacus Insights

Abacus Insights simplifies healthcare data with intelligent solutions, unlocking data value and empowering health plans, consumers, and providers.

Insurance
51-250
Founded 2017
$82M raised
View All Jobs 4

Description

  • Deploy and promote ML and GenAI models, pipelines, and code across environments.
  • Develop reusable deployment patterns and tooling for AI/ML use cases and client deployments.
  • Build and maintain data pipelines from ingestion through feature engineering and serving.
  • Operate Databricks and Snowflake governance, access controls, and environment boundaries.
  • Diagnose and resolve production issues across pipelines, infrastructure, and model-serving systems.
  • Automate and monitor ML inference and feature engineering workflows, including alerting and incident response.
  • Manage model lifecycles using MLflow or similar registries, including tracking, versioning, and promotion.
  • Build RAG infrastructure, vector search pipelines, MCP servers, tool integrations, and AI evaluation systems.
  • Implement observability through logging, tracing, and monitoring of agents and models.
  • Collaborate with engineering, data, security, DevOps, and business teams while mentoring junior engineers.

Requirements

  • 5+ years of experience in AI/ML engineering, MLOps, or a related discipline.
  • Hands-on AI/ML expertise, with depth in GenAI/agentic systems or classical ML and working exposure to the other.
  • Experience with Databricks and/or Snowflake, including ML/AI pipelines and governance frameworks such as Unity Catalog.
  • Strong experience with MLflow or a comparable model lifecycle and registry tool.
  • Proficiency in Python and SQL.
  • Ability to independently diagnose and resolve production infrastructure issues.
  • Experience with agentic frameworks, RAG, vector search, MCP, model serving, or evaluation design.
  • Experience with classical ML algorithms, feature engineering, training pipelines, and production deployment.
  • Strong communication skills and comfort working with non-technical stakeholders.
  • Healthcare, regulated data, multi-agent systems, or Mosaic AI Gateway experience preferred.

Benefits

  • Base salary plus eligibility for performance bonuses and equity grants.
  • Unlimited paid time off.
  • Work-from-anywhere flexibility.
  • Comprehensive health coverage with multiple plan options.
  • Equity for every employee.
  • Growth-focused professional development environment.
  • Home office setup allowance.
  • Monthly cell phone allowance.

Interested in this position?

Apply directly on the company website

Apply Now

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