Responsibilities
- Architect and lead end-to-end ML/AI pipelines — including training, fine-tuning, experimentation, and deployment — setting technical standards across the team.
- Design and own CI/CD pipelines for ML/AI workflows, including automated testing, model versioning, and continuous delivery to production environments.
- Build and maintain scalable ML/AI infrastructure on cloud platforms.
- Develop monitoring and observability frameworks to track model performance, data drift, and system health in production.
- Develop tools and processes that leverage ML/AI to enhance user experience, extract insights from large datasets, and increase operational efficiency.
- Research state-of-the-art ML/AI advancements and translate them into production-ready systems.
- Design, build, and maintain APIs for exposing ML/AI models and data services to internal and external consumers.
- Mentor junior and mid-level data scientists and engineers, conducting code reviews and driving engineering best practices across the ML organization.
- Collaborate with cross-functional stakeholders to scope, prioritize, and deliver high-impact ML/AI solutions.
- Perform other duties as assigned.
Requirements
- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Operations Research, Engineering, or a related quantitative field.
- 5+ years of demonstrated experience developing, training, evaluating, deploying, monitoring, and iterating on production-level ML/AI models and pipelines at scale.
- Solid knowledge of mathematics and statistics underpinning ML methods and model evaluation.
- Experience with large language models (e.g., OpenAI) and applied NLP on unstructured text data, including fine-tuning and deployment of LLM-based systems.
- Strong programming skills in Python, Python-based ML frameworks, and SQL.
- Deep understanding of MLOps principles: deployment, model versioning, experiment tracking, automated retraining, and production observability.
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and ML platform tooling (e.g., SageMaker, MLflow, Kubeflow).
- Experience designing, building, and consuming APIs, including best practices around versioning, authentication, and performance at scale.
- Solid foundation in software engineering principles — writing clean, maintainable, testable, and well-documented code.
- Proficiency with Git/GitHub, including branching strategies and code review workflows.
- Demonstrated ability to lead technical projects, influence architectural decisions, and communicate effectively with diverse, cross-functional teams.
- Comfortable driving results in a fast-paced, rapidly evolving environment.
Benefits
- Flex PTO policy (3-5 wks/year recommended) + 11 paid company holidays.
- Competitive Medical, Dental, Vision, Life, and AD&D insurance.
- Equip pays for a significant percentage of benefits premiums for individuals and families.
- Maven, a company paid reproductive and family care benefit for all employees.
- Employee Assistance Program (EAP), a company paid resource for mental health, legal services, financial support, and more!
- $50/month stipend added directly to an employee’s paycheck to cover home internet expenses.
- One-time work from home stipend of up to $500.
Additional Information
- Work is performed 100% from home with limited travel for team meetings. This is a stationary position that requires the ability to operate standard office equipment and keyboards as well as to talk or hear by telephone. Sit or stand as needed.
