Veeva Systems
1001 - 5000 employees
☁️ SaaS
⚕️ Healthcare Insurance
💊 Pharmaceuticals
SaaS • Healthcare Insurance • Pharmaceuticals
Veeva Systems is a cloud-computing company focused on the global life sciences industry. It provides software, data, and consulting services to streamline research and development, quality management, regulatory operations, and commercial processes. Veeva's solutions encompass clinical trials, regulatory submissions, drug safety management, and commercial execution to support life sciences enterprises in their mission to improve and extend life.
Algorithm Engineer – OpenData
🕒 January 26
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Veeva Systems
1001 - 5000 employees
☁️ SaaS
⚕️ Healthcare Insurance
💊 Pharmaceuticals
SaaS • Healthcare Insurance • Pharmaceuticals
Veeva Systems is a cloud-computing company focused on the global life sciences industry. It provides software, data, and consulting services to streamline research and development, quality management, regulatory operations, and commercial processes. Veeva's solutions encompass clinical trials, regulatory submissions, drug safety management, and commercial execution to support life sciences enterprises in their mission to improve and extend life.
📋 Description
• 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
🏖️ Benefits
• Work Anywhere flexibility • Positive impact on customers, employees, and communities • Support for flexible work from home or in the office • Commitment to balancing interests of stakeholders
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