Insight Global is looking for a motivated Generative AI Engineer to join one of our largest clients in the Pharmaceutical Manufacturing industry. This role is pivotal in optimizing and deploying AI/ML solutions that drive the future of drug development. If you’re excited about revolutionizing AI/ML in the pharmaceutical industry and collaborating with a diverse team of AI/ML scientists, scaling up exploratory work, and transitioning solutions from notebooks to robust ML pipelines, this could be your next career move.

Responsibilities:

• Collaborative Innovation: working directly with AI/ML scientists on optimization and production deployment of solutions, creating blueprints, and acting as an internal consultant to transition ideas from prototype to production.
• Taking Models into Production: Collaborate with data scientists to deploy machine learning models into production environments.
• Data Exploration & Visualization: Exploring and visualizing data to understand those and identify differences in data distribution that could affect model performance when deployed in real-world scenarios.
• Data Quality Assurance: Verifying data quality and ensuring it through data cleaning and ML validation strategies.
• Building training pipelines and components to ensure scalable ML solutions, address errors, and provide education to upskill teams working on ML, enhancing MLOps proficiency.
• Scaling up exploratory work, and transitioning solutions from notebooks to robust ML pipelines

Must Haves:

• Experience as a Generative AI Engineer
• Coming from an ML Engineering background
• Comfortable building out ML infrastructure and deploying ML solutions
• Strong experience building LLMs (large languages models) focusing on fine tuning, pretraining, inference, RAG (Retrieval augmented generation), and building multi-agent workflows
• Using Llamaindex or Langchain
• Experience working in NLP and very comfortable programming in Python and (TensorFlow, PyTorch, HuggingFace, etc) to be able to utilise and work on Deep Learning projects
• Practical knowledge of data tools such as Kubernetes, Databricks or similar
• Experience or understanding of building AI agents
• Background working with technical data scientists, data engineers, and life scientists

Plusses:

• Previous experience working in the Pharmaceutical industry
• PhD focusing on Deep Learning, Neural Networks, Machine Learning or AI