Lead AI/ML Engineer Remote Nationwide or Office-Based in MN/DC
About The Position
The Lead AI/ML Engineer will lead the design, development, deployment, and scaling of enterprise AI/ML solutions that improve clinical outcomes, patient engagement, operational efficiency, and regulatory compliance. This role is responsible for driving engineering best practices, MLOps excellence, and production-scale machine learning solutions while partnering with cross-functional teams to deliver innovative healthcare products leveraging structured and unstructured data. Combining deep technical expertise with technical leadership, this role involves hands-on development, architecture guidance, and mentorship of engineers while enabling enterprise-wide AI adoption. If you are located in MN or DC, you will have the flexibility to work remotely as you take on some tough challenges. This position follows a office-based schedule with four in-office days per week.
Requirements
- Bachelor’s degree or 5+ years of software engineering / machine learning engineering experience in lieu of degree
- 5+ years of software engineering experience across all phases of the Software Development Life Cycle (SDLC)
- 3+ years of experience designing, developing, and deploying production-grade machine learning solutions in cloud environments (Azure, AWS, or GCP)
- 3+ years of programming experience with Python and SQL or PySpark
- 2+ years of experience implementing CI/CD pipelines and automated deployment practices for production software delivery
- Experience working with large-scale distributed data and computing platforms
Nice To Haves
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field
- Experience with enterprise AI/ML platforms such as Databricks, Azure Machine Learning, or Snowflake
- Experience building and deploying Generative AI, Large Language Models (LLMs), NLP, or advanced analytics solutions
- Experience working within regulated healthcare, payer, provider, or clinical environments
- Expertise in MLOps practices including model monitoring, drift detection, model governance, and automated retraining
- Demonstrated ability to lead complex technical initiatives and influence engineering strategy across teams
Responsibilities
- Lead the end-to-end design, development, deployment, and operationalization of production-grade machine learning models and AI-enabled software solutions
- Build and support scalable, cloud-based AI/ML systems, data pipelines, and feature workflows for both batch and real-time workloads
- Establish and drive MLOps practices, including model orchestration, CI/CD automation, testing, drift detection, automated retraining, and operational governance
- Manage, monitor, and optimize production machine learning systems to ensure high reliability, scalability, and performance
- Apply advanced AI/ML techniques—such as Natural Language Processing (NLP), deep learning, computer vision, foundation models, and modern AI architectures—to address complex healthcare challenges
- Provide technical leadership, architecture guidance, and mentorship to engineers while driving engineering excellence across cross-functional teams
- Partner with product management, data science, architecture, and business stakeholders to translate strategic requirements into deliverable AI capabilities and communicate technical approaches to leadership
Benefits
- comprehensive benefits package
- incentive and recognition programs
- equity stock purchase
- 401k contribution
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What This Job Offers
Job Type
Full-time
Career Level
Senior
