Machine Learning Engineering Manager
As a Machine Learning Engineering Manager, you will lead a small team to build out our vision of a novel, best-in-class data science personalization platform to fuel our personalized & data driven healthcare data products. This is a hybrid management / contributor role: you will lead, help architect and support many scalable products that will enhance and personalize the experience of users on the League platform. In addition to writing code, you hold responsibility for identifying bottlenecks in the process and roadblocks to success for their team and clearing these roadblocks.
In this role, you will work as part of a multidisciplinary team that include the Data Platform, Data Science Personalization and Research & Insights teams to establish and evangelize a data and machine-learning driven culture. This team will not only work with the product team closely but will also work with non-engineering functions like Marketing and Business Strategy.
To thrive in this role, you are someone who loves to lead, organize, and operate a team, as well as dives into the hands on work. Furthermore, you oversee the business impact of your team’s work and enjoy measuring and presenting it. You enjoy working with product managers, data scientists, data analysts, data engineers and other stakeholders to orchestrate the best solution to the problem at hand, iterate over it and can balance technical complexity with delivering customer value.
Our platform and applications run on Google Cloud. You and your team will be working on building end to end machine learning products that serve both real-time and batch machine learning pipelines that ingest, split, test, train, re-train and monitor models. You and your team will have an opportunity to leverage new frameworks and paradigms, and freedom to put cutting-edge tech in production to shape the future of digital health!
In this role, you will:
- Monitor day-to-day code delivery and quality, holding the team accountable for upholding our core engineering values
- Have regular 1:1s with team members that discuss both technical work and professional development
- Work with product owners and tech leads to drive successful delivery of our product roadmap
- Lead and mentor data scientists and engineers through the MLOps process and framework, including mentoring data scientists in areas such as software development, lifecycle, & data engineering best practices
- Anticipate and address issues within the team around communication, underperformance, interpersonal dynamics, and unclear ownership
- Utilize a variety of distributed computing frameworks and cloud services and tools to build scalable ML pipelines and endpoints
- Use sound agile development practices (testing and code reviewing, etc.) to develop and deliver data products
- Analyze, tune, troubleshoot and support the MLOps pipelines ensuring the performance, integrity, and security of data and models produced
- Translate business and stakeholder needs into data science questions and requirements, with attention to detail
- Relevant experience in data science, software engineering, data engineering or related discipline.
- Ability to articulate pros and cons of technical decisions and influence stakeholders, and how those decisions will impact delivery timelines.
- Experience with building end to end data science products
- Experience with multiple programming languages – Required: Python, SQL, Nice to Have: Scala, Go, R, C/C++ etc.
- Experience with GCP VertexAI, Azure Machine Learning Studio or AWS SageMaker
- Experience with orchestration tools such as Apache Airflow.
- Experience with developing, implementing, deploying and scaling machine learning models to production.
- Experience in performing root cause analysis of production issues, performance tuning and optimization.
- Experience using and extending ML frameworks and libraries (e.g. TensorFlow, PyTorch, scikit-learn, SHAP)
Nice to have:
- Experience in healthcare datasets like EMR and Claims and interoperability standards like FHIR.
- Experience in a suite of cloud DevOps and CI/CD tools (Terraform, Docker, CircleCI, GitHub Actions, Cloud Build, etc) and processes
- Compliance with Information Security Policies
- Compliance with League’s secure coding practice
- Ensure access management is performed in compliance with the employee's role and responsibilities
- Responsibility and accountability for executing League's policies and procedures within the department/ team
- Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations
CANADA APPLICANTS ONLY: The Canada-specific compensation range below for this full-time position is exclusive of bonus, equity and benefits. This range reflects the minimum and maximum target for base salaries for the position across all Canadian locations. Where in the band you may land is determined by job-related skills/experience and location. Your recruiter can share more about the specific salary range for your location during the hiring process.
- You should receive a confirmation email after submitting your application.
- A recruiter (not a computer) reviews all applications at League.
- If we see alignment with League's needs, a recruiter will reach out to learn more about your goals. The recruiter will also share the team-specific interview process depending on the roles you are exploring.
- The final step is an offer, which we hope you will accept!
- Prior to joining us, we conduct reference and background checks. Additional checks could be required for US Candidates, depending on the role you are exploring.
- Learn about our platform, leadership team and partners
- Highmark Health, Google Cloud, League: new digital front door to seamless care
- Former Providence President and Workday EVP of Corporate Strategy join League Board of Directors
- League raises $95 million USD in Series C to build world’s leading healthcare CX platform
- Forbes x League: The Platformization Of Healthcare Is Here
- Fast Company x League: If we want better innovations in healthtech, we need more competition
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