Senior Generative AI Engineer

Insight Global
London
1 year ago
Applications closed

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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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