Senior ML
Engineer

About this role

You'll work directly with clients and cross-functional teams to build models that solve real business problems — demand forecasting, clinical document understanding, risk scoring, and intelligent process automation. Every model you build ships to production and creates measurable impact.

What you'll do

• Design and implement end-to-end ML pipelines — ingestion, feature engineering, training, evaluation, and serving
• Build and fine-tune models for NLP, structured prediction, and time-series forecasting
• Deploy models to production with monitoring, drift detection, and automated retraining
• Collaborate with data engineers on feature stores and training data pipelines
• Evaluate and integrate LLM-based solutions where they provide clear value
• Establish best practices for experiment tracking, model versioning, and reproducibility

What we're looking for

• 5+ years building and deploying ML models in production
• Strong Python and ML framework experience (PyTorch, TensorFlow, or scikit-learn)
• Cloud ML platform experience (SageMaker, Vertex AI, or Azure ML)
• Solid understanding of MLOps — CI/CD for models, monitoring, and serving infrastructure
• Comfort with messy real-world data and robust preprocessing pipelines
• Ability to explain model trade-offs to non-technical stakeholders

Bonus points

• Experience fine-tuning and deploying LLMs in production
• Background in healthcare, finance, or regulated industries
• Experience building RAG systems
• Contributions to open-source ML projects

What we offer

• Remote-first with async collaboration and flexible hours
• Competitive salary with equity
• Unlimited PTO
• Learning and conference budget
• Home office stipend
• Health, dental, and vision coverage