Senior Software Engineer, Machine Learning
Our mission is to serve cancer patients and our customers by dramatically improving treatment and accelerating research. Our software platform helps physicians manage complex patient treatments in cancer centers. It also empowers life science companies and academic researchers across the country so they can leverage real-world oncology data at a scale and clinical depth never before seen, advance patient care, and accelerate scientific discovery.
As a Senior Software Engineer, Machine Learning, you will:
- Develop machine learning and NLP systems, from conception to design, experimentation, implementation, evaluation, and productionization.
- Tackle some of our hardest and most impactful problems in scaling our ability to efficiently derive insights from patient data.
- Be a leader and mentor in a growing team focused on building machine learning platforms to be used across Flatiron’s business lines.
- Work cross functionally with product managers, oncologists, and statisticians to find the most promising opportunities for machine learning to impact our mission of improving oncology care and research.
- You hold a BS, MS, or PhD in computer science or a related field
- You have at least three years of experience building production systems that use machine learning
- You understand experimental design and can build for collection, measurement, and interpretation of results
- You have experience optimizing the performance, reliability, and scalability of systems
- You value impact, are results-oriented, and care about the details
- You seek simple approaches to complex problems
- You are enthusiastic about working on a multi-disciplinary team
- You are passionate about our mission to improve healthcare through technology
- You have a PhD in computer science or a related field
- You have at least six years of industry experience
- You have experience in natural language processing
- You have experience working with clinical data
- You have led a team
- You have published academic research in machine learning or have contributed to an open-source machine learning software project