Senior Machine Learning Engineer

About You: A Senior Machine Learning Engineer who thrives on first principles problems that no one has ever worked on before. You love innovation and making an immediate impact, and are constantly driving toward launch and delivery thanks to your high degree of ownership and control. You love working on new and challenging problems, not incremental or marginal improvements, and you're supercharged by having interesting, unsolved problems continually present themselves.

In this Role, You Will:

• Build ML models for production use
• Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies
• Suggest and implement new features to improve model performance and business logic
• Write and review production-quality PRs daily
• Translate client business problems into ML problems
• Build scalable machine learning models for claim time series forecasting and NLP text understanding
• Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets

Requirements:

• 2+ years of experience as a Machine Learning Engineer or Data Scientist, preferably in highly scalable production environments.
• You have deep exposure to data science & ML tech stacks (sklearn, Keras / PyTorch, tuning frameworks), data analysis & modeling, feel at home in Python/Pandas/Jupyter, and strive for scalable technical concepts and solutions.
• You have excellent written and verbal communication skills and can effectively correspond between technical and non-technical audiences.
• You’re a team player who is solutions-oriented.
• Experience leveraging Claude Code and related tools is a strong plus

Even Better if You Have the following:

• Knowledge of Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes
• Owned and deployed, and maintained model-serving pipelines in production
• Expert skills at writing clean, efficient, and easy-to-understand code with unit tests and functional design patterns
• Experience with advanced statistical modeling, especially probabilistic programming
• Ambitious, collaborative, and empathetic values
• A work style that is open to giving and receiving critical feedback and collaborating effectively across teams