Veeva2mo ago

Algorithm Engineer - OpenData APAC

SingaporeFull-Timemid

OtherAlgorithm Engineer

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Quick Summary

Overview

Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster.

Technical Tools

OtherAlgorithm Engineer

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 $3B 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.

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.

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)

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

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).