Lead the development of next-generation AI technologies that power clinical trial platforms.
Build scalable data pipelines for AI.
Optimize model performance on hardware accelerators.
Deploy state-of-the-art LLMs and Multi-Modal models.
Collaborate with clinical operations, product, and research teams to translate complex business requirements into robust engineering solutions.
Mentor engineers across the organization, fostering best practices in distributed systems, ML engineering, and the adoption of AI-native development workflows.

Requirements

Bachelor's degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
8+ years of experience in software development with proficiency in Python, C++, or similar languages.
7+ years of experience leading technical project strategy and optimizing industry-scale ML infrastructure (model deployment, evaluation, fine-tuning).
2+ years of experience with state-of-the-art AI techniques (LLMs, RAG, Computer Vision) and frameworks (PyTorch, TensorFlow, JAX).
Demonstrated proficiency in using AI models to augment software engineering practices—specifically using LLMs for code generation, debugging, architectural design validation, and documentation.
Experience designing and scaling data infrastructure, including distributed storage systems, data lakes, or high-performance ETL frameworks.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonC++AI technologiesdata pipelinesmodel performance optimizationLLMsMulti-Modal modelsML engineeringdistributed systemsdata infrastructure

Soft Skills

leadershipmentoringcollaborationcommunicationproblem-solvingstrategic planningbest practices adoptiontranslating business requirements