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Veeva

Posted 58 months ago

Open

Senior Machine Learning Engineer

BarcelonaRemoteFull-time

AI Summary

Senior ML Engineer will build and operationalize AI tools and pipelines in a cross-functional team, delivering scalable ML solutions and genAI capabilities for Veeva Data Cloud.

About this role

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.
As a Work Anywhere company, we support your flexibility to work from home or in the office, so you can thrive in your ideal environment.
Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.

The Role

Veeva Data Cloud is connected data for Life Sciences to accelerate insights and increase efficiency with better data built on a common data architecture.

Within Data Cloud we are the AI team powering the entire suite of products. By building a unified set of AI tools, we enable agility and quality at a global scale. Our state-of-the-art ML and AI models complement the work of more than 3000 data stewards and thereby re-inforce each other. By combining AI with human data stewards, we are able to transform data into actionable insights so that clinical innovation can be developed faster and ultimately more patients can access the treatments they need.

We are looking for someone to work in a cross-functional team of data scientists, engineers and data product managers to productize and scale the AI tools that we build.

Veeva is a work-anywhere company which means you can work in an office or at home on any given day. It’s about getting the work done in the way and place that works best for each person.

What You'll Do

  • Leverage genAI for web research and task automation
  • Build scalable, cost-efficient, and fault-tolerant solutions in AWS or GCP
  • Design, integrate, and optimize end-to-end AI pipelines using a data-driven approach
  • Develop and manage ML infrastructure and CI/CD pipelines to support data products
  • Provide engineering mentorship and guidance to data scientists
  • Collaborate with ML engineers, data engineers/scientists, product, and operations teams
  • Partner with data quality teams to develop data annotation and evaluation pipelines, monitoring solutions, and dashboard

    • Requirements

  • Proven ability to take ideas into a production system at scale with cost effective emphasis
  • Experience in genAI frameworks and agentic development
  • Experience with asynchronous and batch APIs for GenAI, web search etc.
  • 4+ years of experience in professional software development, with solid programming skills ­in Python and excellent debug abilities
  • 2+ years of experience in cloud development preferably in AWS
  • 2+ years of experience as a Machine Learning Engineer or relevant jobs
  • Up-to-Date knowledge of the latest ML innovations and frameworks
  • Experience in infrastructure automation and provisioning using Terraform or equivalent Infrastructure-as-Code (IaC) tools
  • Professional in ML Operationalization, including workflow/model management platforms
  • Great skills in Data Engineering including data pipelines and ETLs
  • Experience in containerization, Kubernetes, and relevant distributed computing for training and inference
  • Strong collaboration skills and good verbal and written communication skills in English

    • Nice to Have

  • Experience in the life/health science industry, notably pharma
  • Great skills in big data technologies such as Spark
  • Experience with Vector databases & NoSQL
  • Familiarity with architectural choices, particularly for ML systems
  • Crawling/Webscraping, specially with AI tools

    • Perks & Benefit

  • Work anywhere
  • Veeva charitable giving program
  • Fitness reimbursement
  • Life insurance + pension fund

    • Skills

    Agentic DevelopmentAsynchronous APIsAWSBatch APIsCI/CDCI/CD PipelinesCloud InfrastructureData AnnotationData GovernanceData PipelinesData QualityDistributed ComputingDockerETLETL PipelinesGCPGenAI FrameworksInfrastructure AutomationKubernetesMLflowMLOpsModel ManagementNoSQLPythonSparkTerraformVector DatabasesWeb Crawling

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