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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI/ML technologies, including deep learning and generative AI, while applying strong software engineering practices and a responsible-AI mindset. Proven ability to communicate complex research findings to diverse audiences and coordinate effectively with cross-functional teams.
Highest-signal resume keywords
AI/ML ResearchPython ProgrammingDeep LearningGenerative AIResponsible-AI Mindset
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/ML TechnologiesDeep LearningGenerative AIReinforcement LearningMultimodal LearningLarge-Scale DatasetsCloud-Based ComputingSoftware Engineering PracticesExperimental MethodologyEvaluation Metrics
Soft Skills
CommunicationCoordinationCross-Functional Collaboration
Tools & Technologies
AI/ML LibrariesCI/CD PipelinesResearch Infrastructure
Industry Keywords
Model SafetyReliabilityRisk ManagementRegulated EnvironmentsTechnical Strategy
Tech Stack
Tools & technologiesCloudPython
About the role
Key responsibilities & impact- Research, design, develop, prototype, and validate novel AI/ML technologies
- Translate emerging scientific advances into opportunities for future product innovation
- Build reusable, high-quality research and prototype code
- Investigate foundation models, multimodal learning, and time-series modeling
- Define evaluation metrics, benchmarks, and monitoring; identify risks and drive mitigations
- Lead technical strategy balancing model performance, latency, cost, safety, and regulatory requirements
- Publish and present research at leading conferences and journals
- Communicate complex methods and results to technical and non-technical audiences
- Coordinate with R&D, Commercial, Product, Legal, and Regulatory stakeholders
- Build and improve research and training infrastructure, including data, experimentation, and CI/CD pipelines
- Apply reliability, observability, and cost-awareness to accelerate research
Requirements
What you’ll need- Typically requires a Bachelor’s degree in a technical discipline and a minimum of 5-8 years related experience, or Master’s degree and 2-5 years equivalent industry experience, or a PhD and 0-2 years experience
- Strong CS fundamentals
- Hands-on experience with Python and modern AI/ML libraries and frameworks
- Depth in deep learning, generative AI, reinforcement learning, and multimodal learning
- Experience independently conducting rigorous AI/ML research
- Experience with large-scale datasets
- Experience with cloud-based and distributed computing environments
- Strong software engineering practices and sound experimental methodology
- Responsible-AI mindset attentive to model safety, reliability, and risk in regulated, high-stakes settings
- Demonstrated record through conference publications, journal articles, patents, invited talks, or open-source contributions
- Ability to coordinate with cross-functional stakeholders
- Willingness to travel 5-15%
Benefits
Comp & perks- A full and comprehensive benefits program
- Growth opportunities on a global scale
- Access to career development through in-house learning programs and/or qualified tuition reimbursement
- Home office workplace
- Hybrid working environment may be available for employees within commuting distance of a Dexcom site
- Flex workplace option