Job Description

The Role


Veeva OpenData Commercial supports the industry by providing reference data across the complete healthcare ecosystem, to support commercial sales execution, compliance, and business analytics. We drive value to our customers through constant innovation, using cloud-based solutions and state-of-the-art technologies to deliver product excellence and customer success.
This role is critical in creating ML and AI processes to power next-generation data collection.

What You’ll Do

  • Work within a cross-functional data team to build scalable NLP and ML models
  • Work from end-to-end on live production pipelines. Not just modeling, not theoretical
  • Define the best approach to solve problems with ML. Build data and model pipelines
  • Test, validate, deploy, and monitor solutions for impact
  • Optimize models for production throughput and uptime requirements
  • Automate deployments, testing, and monitoring (MLOps)

    • Requirements

  • 2+ years of hands-on experience in a Machine Learning Engineer, Algorithm Engineer, or similar role
  • Expert-level proficiency in Python, with strong experience in building production-ready ML code
  • Solid foundation in machine learning concepts, including model training, evaluation, and optimization
  • Practical experience with deep learning or ML frameworks, such as PyTorch,
  • TensorFlow, or related libraries (e.g., TRL for reinforcement learning or fine-tuning workflows)
  • Familiarity with modern MLOps practices, including experiment tracking, model versioning, and deployment, using at least one platform such as MLflow,
  • Kubeflow, or AWS SageMaker
  • Strong problem-solving ability and the capacity to work both independently and collaboratively
  • Strong communication skills, with the ability to explain tech

    • Nice to Have

  • Experience with cutting-edge AI techniques, such as: Agentic AI / Autonomous Agents, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs) and fine-tuning approaches
  • Exposure to end-to-end ML systems, including data ingestion, model serving, monitoring, and automated retraining.
  • Experience working in cloud environments (AWS, GCP, or Azure).
    • Veeva’s headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world.

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