Senior/Lead AI Engineer

Key Responsibilities

• AI Leadership & Strategy
• Define and execute the AI strategy for next-generation lab operations.
• Drive adoption of Generative AI, deep learning, and automation to optimize workflows.
• Lead R&D in:
• Retrieval-Augmented Generation (RAG)
• Prompt engineering
• LLM fine-tuning and optimization
• Deliver AI-powered solutions for:
• Smart task list generation
• Contextual workflow guidance
• Intelligent lab automation
• Assess and integrate emerging AI technologies for real-world lab environments.
Advanced AI & Machine Learning Engineering
• Architect and scale AI systems using AWS Bedrock, SageMaker, PyTorch, TensorFlow, and Scikit-learn.
• Fine-tune custom LLMs for workflow automation and enhanced decision support.
• Build real-time AI applications with predictive insights and contextual recommendations.
• Apply MLOps best practices for:
• Automated model training
• Validation
• CI/CD deployment pipelines
Software Engineering & Intelligent UX
• Develop end-to-end AI applications integrating:
• Workflow automation
• Task management
• Decision support systems
• Design AI-enhanced UIs and dashboards that guide lab personnel through complex procedures.
• Contribute to both frontend and backend development for a seamless AI-powered user experience.
Cross-Functional Collaboration & Thought Leadership
• Collaborate with data scientists, engineers, and lab experts to design practical AI solutions.
• Lead internal and partner teams in Generative AI application delivery.
• Evangelize AI/ML innovation to both technical and business stakeholders.
• Champion ethical and compliant AI practices aligned with healthcare and life sciences regulations.
• Client-facing and ability to own the process and adapt to changes.

Qualifications

• Required Experience
• 8+ years in software development with a strong focus on AI/ML.
• Deep expertise in Python, Java, SQL, and frameworks like PyTorch, TensorFlow, Keras, and Scikit-learn.
• Proven hands-on experience in:
• Generative AI systems
• LLM fine-tuning
• RAG (Retrieval-Augmented Generation)
• 8+ years deploying machine learning models in production using platforms like AWS SageMaker or Bedrock.
• Demonstrated success in:
• Workflow automation
• Building real-time AI applications
• Optimizing cloud-based infrastructure
• Strong grasp of MLOps, scalability, and cloud (AWS) best practices.
• Strategic thinker with a builder’s mindset and an innovation-first approach.
Preferred Qualifications
• Experience working with LIMS/LES systems and lab automation tools.
• Familiarity with healthcare and life sciences regulatory requirements (e.g., HIPAA, GxP).
• Background in designing secure and compliant AI solutions for regulated environments.

Why Join Us?

• Be at the forefront of AI innovation in life sciences. Your work will directly impact the future of laboratory intelligence, enabling groundbreaking efficiencies and smarter scientific discovery. You’ll join a collaborative and forward-thinking team where your expertise will drive real-world transformation.