About this role
Yahara Software seeks a Lead Machine Learning Engineer to lead the technical delivery of client projects for life sciences and scientific instrumentation organizations. The role is hybrid, based out of its Madison, Wisconsin office.
Responsibilities
- Design, train and evaluate models for applications including classification, forecasting and anomaly detection. Choose among classical machine learning, deep learning, pretrained models and custom models according to the problem.
- Prepare messy client data and engineer useful features; define measures of model performance. Partner with DevOps to deploy, monitor and retrain models in production.
- Set project teams’ technical direction and own delivery quality and pace. Mentor engineers through code reviews and collaborative problem-solving. Explain results, tradeoffs and risks to clients; contribute solution outlines and rough estimates to pre-sales discussions; and document key decisions in architecture decision records.
- Apply sound methodology, rigorous testing and sound architecture. The team uses AI development tools such as Claude and Codex where useful while retaining responsibility for code quality, accuracy and understanding.
Required background:
- 6+ years in software engineering, data science or ML engineering; hands-on experience building and training ML models that shipped; experience leading technical work, formally or informally; and a broad ML toolkit.
- Ability to make decisions amid uncertain data or requirements, assess model limitations honestly, develop other engineers and communicate technical tradeoffs to non-technical stakeholders.
Preferred background includes life sciences, lab systems or regulated scientific software; computer vision, NLP or time-series modeling; MLOps practices such as experiment tracking and model versioning; consulting or client-facing projects; and Azure or AWS cloud ML certifications. Example technologies—not requirements—include Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, XGBoost, MLflow, Weights & Biases, Azure Machine Learning, Amazon SageMaker, Docker and Kubernetes.
This is a full-time salaried position. Candidates must be permanently eligible to work in the U.S.; sponsorship is unavailable. Stated benefits include 20+ days of first-year accruable PTO, health coverage, an employer-funded HSA, a matched 401(k), company-paid disability and life insurance, a home-office stipend and a certification bonus program.