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Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Devising and applying state-of-the-art machine learning, deep learning, and modern AI techniques (including Generative AI, LLMs and Multimodal AI) to solve business and scientific problems
- Evaluate AI/ML readiness and provide data acquisition recommendations to bridge gaps
- Build production-grade machine learning solutions, not just prototypes
- Own the development of end-to-end AI/ML projects, including deployment into production environments, and monitoring for continuous improvement
- Design, develop, and maintain software components of internal data science platforms, enabling chemists, engineers, and business users to leverage AI/ML models through intuitive tools, APIs, and applications
- Communicate findings, assumptions, and model performance to both technical and non-technical stakeholders
Requirements
What you’ll need- Ph.D. in Data Science, Computer Science, Engineering, Chemistry, Physics, or related field
- 5+ years of experience delivering AI/ML solutions in production environments
- Strong expertise in: Machine learning and deep learning
- Statistical modeling and optimization
- Python and modern ML frameworks
- Proven experience building scalable, production-grade ML systems
- Experience working in Agile or product-oriented teams
Benefits
Comp & perks- Health insurance
- Professional development opportunities
- Flexible working hours
- Paid time off
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdeep learningGenerative AILLMsMultimodal AIstatistical modelingoptimizationPythonML frameworksproduction-grade ML systems
Soft Skills
communicationcollaborationproblem-solvingstakeholder engagementcontinuous improvement
Certifications
Ph.D. in Data SciencePh.D. in Computer SciencePh.D. in EngineeringPh.D. in ChemistryPh.D. in Physics
