Senior Generative AI Engineer
5 days ago
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
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