[Hiring] Associate AI/ML Engineer @UnitedHealth Group

Role Description

We are seeking an Associate AI/ML Engineer (early‑career) who is excited to grow in a supportive, collaborative environment. You’ll be set up for success with clear expectations, opportunities to pair with senior engineers, and mentorship as you learn‑by‑doing—contributing to AI services, exploring Generative AI, and building foundational skills across machine learning and data engineering. We value curiosity, steady progress, and thoughtful questions as much as technical output.

You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• AI/ML Solution Development
  • Implement and iterate on AI and machine learning solutions (including Generative AI) by building prototypes, integrating models into services, and improving quality based on evaluation results.
• Model Training, Evaluation & Optimization
  • Support proof‑of‑concepts and model experiments and help baseline performance using clear evaluation metrics (with guidance on approach and tooling).
• Platform & Infrastructure Engineering
  • Contribute to training and inference pipelines using Databricks, PySpark, and cloud platforms (AWS, Azure, GCP) with guidance from senior engineers.
• Generative AI & Advanced Techniques
  • Learn and apply GenAI building blocks such as RAG and prompt orchestration tools (e.g., LangChain); exposure to vector databases is a plus.
  • Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI.
  • Support performance and cost improvements (e.g., caching, batching, basic optimization), and learn model optimization techniques (quantization/distillation) as needed.
• Software Engineering & APIs
  • Contribute to building and testing APIs (e.g., REST with FastAPI) and learn delivery fundamentals such as containers (Docker) and simple app frameworks (e.g., Flask/Streamlit) as needed.
• Collaboration & Communication
  • Collaborate with cross‑functional partners to understand business needs, ask clarifying questions, and communicate progress and results clearly.
• Leadership, Mentorship & Culture
  • Participate in design and code reviews, learn from feedback, and contribute to team standards for quality, safety, and trust.

Qualifications

• Bachelor’s degree in Computer Science, IT, Data Science, or a related field.
• 1+ years of software engineering experience (including internships, co‑ops, academic, or personal projects) delivering well‑tested applications and services.
• 6+ months of AI/ML engineering experience, including prototyping, evaluation, and supporting deployment/monitoring in collaboration with senior engineers.
• 6+ months of hands‑on experience (coursework, internships, or projects) with Python and SQL; familiarity with Java and scripting is a plus.
• 6+ months of experience with any one major cloud platform (AWS, Azure, or GCP) through internships, labs, or projects or professional experience.

Preferred Qualifications

• Familiarity with MLOps concepts (experimentation tracking, model packaging, deployment patterns, and monitoring basics).
• Exposure to Infrastructure as Code tools such as Terraform or CloudFormation (learning‑level or project experience).
• Awareness of data governance and access control concepts; familiarity with Databricks features like Delta Lake and Unity Catalog is a plus.
• Familiarity with common AI/ML libraries and basic patterns for integrating models into applications (inference, evaluation basics, and logging/monitoring fundamentals).
• Exposure to big data technologies such as Spark; familiarity with ecosystem tools (e.g., Kafka/Hadoop) is a plus.
• Basic understanding of data science fundamentals (statistics/probability, metrics, and data modeling); deeper coursework or hands‑on project experience is a plus.
• Exposure to Databricks and Spark (PySpark/SparkSQL) through coursework, projects, or professional experience; familiarity with building basic data pipelines is a plus.
• Familiarity with distributed data processing concepts (batch/streaming fundamentals, data partitioning, and performance basics).
• Foundational understanding of clean, maintainable code, debugging, and basic API/service concepts; eager to learn system design and modern engineering best practices.
• Ability to design, build, deploy, and operate production‑ready services with guidance, including exposure to CI/CD and cloud infrastructure.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.