Develop scalable, production-ready LLM applications using frameworks like LangChain/LangGraph
Build robust RAG pipelines and integrate knowledge graphs for biological and clinical data
Write maintainable, high-performance code and build clean APIs and services for machine learning applications
Work with data engineers to build and optimize data workflows and pipelines for high-quality data ingestion and processing
Collaborate with product and domain teams to rapidly prototype AI solutions, iterate based on feedback, and scale models for production
Use modern MLOps tools to deploy and monitor models in production environments (AWS preferred)
Partner with engineering, data, and business teams to identify and develop high-value AI/ML applications
Stay ahead of the curve on emerging ML frameworks, GenAI capabilities, and healthcare technologies

Bachelor's, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, or a related field
Proven ability to build, train, and deploy ML and NLP models, especially those powered by LLMs and transformer architectures
Practical experience working with frameworks like LangChain for applications such as Q&A systems, chatbots, or document automation
Strong coding skills in Python and experience using Git/GitHub and CI/CD practices
Comfort working with ETL pipelines, relational and non-relational databases, and data platforms like Snowflake or Databricks
Familiarity with Big Data tools (e.g., Apache Spark) and experience orchestrating data workflows using tools like Apache Airflow
Experience with deploying ML models in cloud environments (AWS, GCP, or Azure) and using containerization/orchestration tools like Docker and Kubernetes
Strong problem-solving skills and an analytical mindset
Passion for continuous learning, rapid prototyping, and iterating based on user needs
Autonomous, self-starter attitude with a strong sense of ownership
Excellent communication skills—able to explain technical ideas clearly to non-technical audiences
Collaborative team player with a desire to build things that truly matter
Bonus: Experience in healthcare, life sciences, or biopharma sectors (preferred but not required).

Senior AI / ML Engineer

Key skills