The Machine Learning team at UPMC Enterprises collaborate in cross-disciplinary teams to rapidly solve impactful problems in healthcare with our deep knowledge of modern machine learning technologies and innovative data analytics. We work directly with our colleagues in product and engineering, our stakeholders across UPMC payor and provider sides of healthcare, and key healthcare start-ups to better patient lives.
Healthcare is a rich, highly specialized domain, with varied data modalities and no shortage of challenging problems. The ML team uses techniques from a wide range of fields, including natural language processing over clinical notes, computer vision for medical images, and working with timeseries data such as a history of lab test results. Future possible projects may include speech data of medical conversations or genomics data. We work with both data-at-scale and data deficient settings.
Open to full-time remote.
The Lead Machine Learning Engineer is a highly regarded independent contributor and a technical leader in the team. They are influential across teams and are respected as a technical expert.
- Work with massive quantities of real-world healthcare data while following organizational processes around HIPAA compliance to safeguard private patient information.
- Use deep expertise in Machine Learning to help evaluate new healthcare technology.
- Be expected to stay current with the state of the art in Machine Learning research.
- Own and drive the lifecycle of developing new Machine Learning technology with a high degree of autonomy.
- Collaborate in an interdisciplinary and cross-functional project team.
- Work with product managers and stakeholders to define the problem and its requirements.
- Perform data analysis and preprocessing in massive quantities of real-world healthcare data.
- Research state-of-the-art methods, develop hypotheses, implement models, and develop necessary tooling required for the project.
- Evaluate approaches with appropriate metrics, communicate results to stakeholders for feedback, and incorporate feedback in tight iterative loops while meeting project deadlines.
- Collaborate with engineering to productionize models.
- Exercise excellent oral and written communication skills conveying new ideas to our team and in touchpoints with product managers, healthcare experts, and our partners in healthcare start-ups.
- Demonstrate high initiative and are self-driven to excellence.
- Embody a growth-mindset and are excited to receive feedback and continuously learn to deepen their understanding of ML and improve interpersonal skills.
- Demonstrate deep understanding in multiple areas of ML and combine ideas from multiple fields to develop novel, state of the art solutions.
- Mentor junior members of the team and help them develop their technical and soft skills, promoting their growth and independence.
- Understand the technical strengths and weaknesses of junior team members and take an active role in their guiding their growth.
- Technically lead projects involving multiple ML Engineers.
- Act as key contributor in defining project scope, requirements, technical roadmap, and timelines in collaboration with stakeholders and product management.
- While developing project scope, identify gaps in necessary technical knowledge and rapidly come up to speed with the appropriate new technology and new fields of ML to help define technical direction and scope.
- Identify areas of opportunities to define and lead forward-looking team-wide initiatives in ML.
- Manage competing priorities of owning technical delivery for multiple projects while meeting deadlines.
- Communicate and create consensus across teams for technical proposals to move projects forwards.
- Create compelling narratives to communicate project outcomes and technical insights to stakeholders and senior leadership.
- Educate and contribute ML knowledge across the organization.
- Bachelor’s degree in computer science, computational biology, applied math, or other similar quantitative field
- Prefer MS or PhD in machine learning related fields
- Highly knowledgeable in multiple subfields of ML and able to combine ideas from multiple fields to solve problems
- Proficient in software development and understanding of coding best practices, including familiarity with code reviewing, version control systems, good code hygiene, documentation etc.
- Demonstrated track record of developing novel, state of the art ML methods
- Track record of successfully leading teams to deliver impactful ML solutions that result in significant value creation
- Experienced in communicating and creating consensus around technical ideas with a wide variety of technical and non-technical audiences, including executive-level leadership
- Experience in solving problems in healthcare or biomedical settings
- Experience in working with varied data modalities, including time series, images, natural language text, genomics, speech, etc.
- Cloud-based development experience
- Experience in working with problems in both data-deficient and large-scale data settings
- Experience in working within cross-disciplinary and cross-functional teams
- Prefer 7+ years of relevant experience
Licensure, Certifications, and Clearances:
UPMC is an Equal Opportunity Employer/Disability/Veteran