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Tech Stack
Tools & technologiesPySparkPythonSQL
About the role
Key responsibilities & impact- The Senior AI Engineer (Specialist) plays a pivotal role in designing, developing, and deploying GenAI/LLM, NLP and agentic AI solutions.
- Collaborates with cross-functional teams to transform structured + unstructured healthcare data into LLM-enabled products.
- Responsible for end-to-end delivery for AI workstreams from scoping to deployment/ monitoring.
- Leads feature engineering strategy; mentors juniors and performs code reviews on top of being hands on.
- Build and maintain reusable ML accelerators for standardization.
Requirements
What you’ll need- Bachelor’s or master’s degree in computer science, Engineering, Machine Learning, NLP, or related field.
- ~8–10 years of industry experience building production systems (with at least 2–3 years in NLP/LLM or applied ML engineering).
- Strong proficiency in Python/ Pyspark and SQL for working with large, complex datasets.
- Experience in defining evaluation taxonomies and acceptance criteria across initiatives.
- Strong knowledge of neural network patterns, specifically Transformer architectures, Large Language Models (LLMs), and Small Language Models (SLMs).
Benefits
Comp & perks- Do meaningful work with us.
- Competitive health insurance.
- Professional development opportunities.
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
PythonPysparkSQLNLPGenAILLMagentic AIfeature engineeringneural network patternsTransformer architectures
Soft Skills
collaborationmentoringcode reviewsleadership
Certifications
Bachelor’s degreeMaster’s degree
