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Senior Principal Engineer

2 months ago

Boston, Massachusetts, United States Vertex Pharmaceuticals Full time
Job Title: Senior Principal Engineer

We are seeking a highly skilled Senior Principal Engineer to lead and manage our critical Machine Learning and Artificial Intelligence Platform. As part of the Data & Software Engineering (DSE) Team, you will be responsible for developing and maintaining the infrastructure and tools required for the deployment, monitoring, and continuous improvement of machine learning models.

Key Responsibilities:
  • Platform management: Manage, maintain, and improve Vertex's ML platform with a focus on security, DevOps, and enabling best practices for users to design, implement, and manage end-to-end ML pipelines.
  • Technology expert: Accountable for developing, deploying, and maintaining Vertex Data Platform components that enable and support the full development and deployment cycle for advanced Machine Learning and Artificial Intelligence solutions.
  • Delivery management: Estimate, architect, and execute on delivery of critical projects and solutions, in partnership with the DSE leadership team, that support and enable data scientists.
  • Operations Management: Manage and partner with a team of MLOps and Data Engineers to maintain the Vertex Data Platform. Troubleshoot and resolve issues related to model deployment, execution, and performance.
  • Innovation champion: Advocate for process enhancements and opportunities to improve our ML and Data Science capabilities. Partner closely with Director, Data Platforms for defining, architecture, and designing AI/ML platform components. Collaborate with data scientists and data engineers to integrate best practices into the development lifecycle.
Qualifications:
  • 8-10 years of experience working as a Software Engineer, DevOps Engineer, MLOps Engineer, or Machine Learning Engineer within a production ecosystem.
  • 3+ years working in an MLOps or ML Engineering role leveraging Databricks, AWS, or equivalent cloud data platforms.
  • Demonstrated experience with model pipeline technologies like Astronomer/Airflow, MLFlow, etc.
  • Demonstrated experience in developing (or supporting) ML/AI solutions leveraging Python libraries such as PyTorch, Tensorflow, XGBoost, etc.
  • Demonstrated experience monitoring and optimizing the security and performance of deployed models.
  • Experience automating model training, validation, and deployment processes to enhance efficiency and reproducibility.
  • Demonstrated experience working in agile environments (5+ years).
  • Demonstrated ability to work independently and manage multiple projects that require collaboration across functional areas.
  • Skillful, collaborative team player able to develop rapport and credibility with stakeholders.
  • Demonstrated ability and willingness to teach, engage, and support others as they learn new technologies and concepts.
  • Enthusiasm for and the ability to quickly learn new technologies and tackle difficult problems.
  • Strong presentation, verbal, and written communication skills.
  • Working knowledge of key workflow tools, including JIRA and Confluence.

Vertex Pharmaceuticals is a global biotechnology company that invests in scientific innovation. We are committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition.