Lead Machine Learning Engineer
Know your way around a model from first dataset to final evaluation? Come lead a team building machine learning that solves real problems for life sciences and scientific instrumentation clients.
Important Notes about this Position:
- This is a hybrid position based out of our office in Madison, WI.
- We are unable to provide sponsorship.
The Opportunity:
You'll lead the technical side of client projects where machine learning is the heart of the solution. Some days that means training a model from scratch. Other days it means picking the right existing model and making it earn its keep. You'll set the technical direction, grow the engineers around you, and work alongside our DevOps team to get models running in production.
Our Approach:
We build on strong engineering fundamentals: solid methodology, rigorous testing, and sound architecture. We use AI tools like Claude and Codex where they speed up delivery, while keeping critical thinking and engineering discipline at the center. We own the quality, accuracy, and understanding of the code we ship.
What You'll Do:
- Design, train, and evaluate models for classification, forecasting, anomaly detection, and more.
- Choose the right approach for the problem, from classical ML to deep learning.
- Decide when a pretrained model beats a custom one, and explain why.
- Shape messy client data into features a model can actually learn from.
- Define how models get measured, so everyone knows what "good" looks like.
- Partner with DevOps to deploy, monitor, and retrain models in production.
- Own technical delivery for your project team: quality, pace, and direction.
- Mentor the engineers on your team through code reviews and one-on-one problem solving.
- Help engineers work through hard problems instead of solving them for them.
- Present results, tradeoffs, and risks to clients in plain language.
- Join pre-sales conversations with solution outlines and rough estimates.
- Document key decisions in ADRs so the next team knows why, not just what.
What You'll Bring:
Experience:
- 6+ years in software engineering, data science, or ML engineering.
- Hands-on experience building and training ML models that shipped.
- Time leading technical work for a team, formally or informally.
- A broad ML toolkit rather than a single narrow specialty.
Mindset:
- Comfort making sound calls when the data or requirements are fuzzy.
- Honesty about what a model can and can't do.
- Genuine interest in helping other engineers grow.
- Ability to explain technical tradeoffs to non-technical stakeholders.
Nice to Have:
- Experience with life sciences organizations, lab systems, or regulated scientific software.
- Computer vision, NLP, or time-series modeling.
- MLOps practices like experiment tracking and model versioning.
- Consulting or client-facing project experience.
- Cloud ML certifications (Azure or AWS).
Tech Like What You'll Use (examples, not requirements; we're stack agnostic):
- Python and its data ecosystem (pandas, NumPy)
- ML frameworks like scikit-learn, PyTorch, TensorFlow, or XGBoost
- Experiment tracking like MLflow or Weights & Biases
- Cloud ML platforms like Azure Machine Learning or Amazon SageMaker
- Containerization (Docker, Kubernetes)
Company Benefits & Perks
- 20+ days of PTO accruable in the first year!
- Comprehensive health insurance (Medical, Dental, Vision) with HMO and PPO options
- Health Savings Account (HSA) with annual employer contributions
- 401(k) with guaranteed company match (Traditional and Roth options)
- 100% company-paid short-term and long-term disability
- 100% company-paid life insurance with option to increase coverage
- 100% company-paid identity theft protection
- On-site gym with basketball court
- Hybrid/remote schedule with home office stipend
- Fresh fruit, healthy snacks, and beverages provided daily
- Bonus certification program (Microsoft, AWS, PMP, IIBA, etc.)
- Employee Assistance Program (counseling, legal, financial services)
- Monthly and Quarterly Recognition Awards with spot bonuses
- Company-supported community outreach and volunteer opportunities
- Employee-run committee involvement opportunities
- Collaborative culture founded on realized values and incredible people
This is a full-time, salaried position with competitive salary and benefits. Candidates must be eligible to work in the U.S. on a permanent basis and can work on-site in our office located in Madison, Wisconsin.
