The role involves building scalable NLP and ML models, defining approaches for ML problems, optimizing models, and automating deployments with MLOps practices.
Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, we surpassed $2B in revenue in our last fiscal year with extensive growth potential ahead.
At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.
Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.
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.
Veeva is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics protected by local laws, regulations, or ordinances.
Top Skills
Aws Sagemaker
Kubeflow
Mlflow
Python
PyTorch
TensorFlow
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