Senior AI/ML Engineer
Sarepta Therapeutics
August 26, 2026
Remote friendly (Cambridge, MA)
United States
IT
The Opportunity to Make a Difference
- Use Case Delivery and Implementation: Design, build, and deploy scalable machine learning models embedded in real workflows with measurable outcomes.
- Solution Evaluation and Implementation: Evaluate internal and vendor AI/ML technologies to meet scientific/business requirements and align with approved platforms.
- Cross-Functional Collaboration: Partner with R&D, Clinical Operations, Regulatory Affairs, and others to translate needs into data science questions and production solutions; provide guidance and enablement.
- Data and Infrastructure: Partner with IT, Enterprise Data Systems (EDS), and data engineering to ensure availability, quality, and governed use of data.
- Governance and Traceability: Ensure outputs are explainable where appropriate, traceable, reproducible, and aligned with governance/validation expectations and enterprise data governance standards.
- Innovation and Research: Stay current on AI/ML/data science advances and apply practical approaches to business challenges.
More About You
Education:
- Master’s or Ph.D. in a quantitative field (Computer Science, Data Science, Statistics, Computational Biology, or related).
Experience:
- 5+ years; 3+ years hands-on data science/ML with a track record of developing/deploying AI/ML models in a corporate environment.
- Experience in fast-paced, evolving environments and cross-disciplinary collaboration.
Technical Skills:
- Proficiency in Python or R.
- ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
- Strong SQL; experience with relational and non-relational databases.
- Cloud experience, preferably AWS and Snowflake.
- Software engineering best practices: Git, testing, CI/CD.
Preferred:
- Biopharmaceutical/biotechnology industry experience.
- Drug discovery/development familiarity.
- Life sciences data sources (genomic, clinical trial, real-world evidence).
- GxP regulations knowledge/regulated environment experience.
Application:
- Candidates should apply if comfortable with ambiguity and candor and able to work with kindness/integrity.
- Hybrid role; work onsite at US facilities and attend in-person events as needed.
- Target salary range: $152,400–$190,500/year.
- Use Case Delivery and Implementation: Design, build, and deploy scalable machine learning models embedded in real workflows with measurable outcomes.
- Solution Evaluation and Implementation: Evaluate internal and vendor AI/ML technologies to meet scientific/business requirements and align with approved platforms.
- Cross-Functional Collaboration: Partner with R&D, Clinical Operations, Regulatory Affairs, and others to translate needs into data science questions and production solutions; provide guidance and enablement.
- Data and Infrastructure: Partner with IT, Enterprise Data Systems (EDS), and data engineering to ensure availability, quality, and governed use of data.
- Governance and Traceability: Ensure outputs are explainable where appropriate, traceable, reproducible, and aligned with governance/validation expectations and enterprise data governance standards.
- Innovation and Research: Stay current on AI/ML/data science advances and apply practical approaches to business challenges.
More About You
Education:
- Master’s or Ph.D. in a quantitative field (Computer Science, Data Science, Statistics, Computational Biology, or related).
Experience:
- 5+ years; 3+ years hands-on data science/ML with a track record of developing/deploying AI/ML models in a corporate environment.
- Experience in fast-paced, evolving environments and cross-disciplinary collaboration.
Technical Skills:
- Proficiency in Python or R.
- ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
- Strong SQL; experience with relational and non-relational databases.
- Cloud experience, preferably AWS and Snowflake.
- Software engineering best practices: Git, testing, CI/CD.
Preferred:
- Biopharmaceutical/biotechnology industry experience.
- Drug discovery/development familiarity.
- Life sciences data sources (genomic, clinical trial, real-world evidence).
- GxP regulations knowledge/regulated environment experience.
Application:
- Candidates should apply if comfortable with ambiguity and candor and able to work with kindness/integrity.
- Hybrid role; work onsite at US facilities and attend in-person events as needed.
- Target salary range: $152,400–$190,500/year.