Senior Machine Learning Engineer (Remote)

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 apublic benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.

As aWork Anywhere company, we support your flexibility to work from home or in the office, so you can thrive in your ideal environment.

Join us intransforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.

The Role

We are an AI team supporting the entire suite of link data products (e.g.,Link Key People). Agility and quality are our operating principles in developing cutting-edge ML models. Our ML models are trained by data captured by a massive group of over 1900 subject-matter experts. ML models complement the curational pipeline and scale our solutions to different regions, languages, and therapeutic areas. Ultimately, we accelerate clinical trials and equitable care. We are proud that our work helps patients to get their most urgent care sooner. See us in this video and learn why you may prefer to join us here.

What You’ll Do

• Technical lead for ML-Ops
• Develop and manage ML infrastructures and CICD pipelines to support multiple data products
• Provide engineering mentorship and guidance to data-scientists
• Collaborate with ML engineers, data scientists, data engineers, and product and operation teams
• Develop, integrate, and optimize end-to-end AI pipelines by a data-driven approach
• Build fully automated, scalable, cost-effective, and fault-tolerant solutions in AWS to process billions of records
• Collaborate with data quality teams to build data annotation/evaluation pipelines, monitoring, and dashboards

Requirements

• Strong collaboration skills as well as verbal and written communication skills
• Professional in ML Operationalization, including workflow/model management platforms such as Airflow/MLflow
• 4+ years of experience in professional software development
• 2+ years of experience as a Machine Learning Engineer or relevant jobs
• 2+ years of experience in cloud development
• Solid programming skills in Python
• Great skills in Data Engineering and big data technologies such as Spark
• Up-to-Date knowledge of the latest ML innovations and frameworks
• Strong analytical skills and data curiosity
• This position is listed identically as remote work in Germany and Netherlands. Before applying, you must already live in the above countries and be legally authorized to work there without requiring Veeva’s support for a visa. If you need a Visa, plan to relocate, or intend to work in a nearby country, please submit an additional document explaining your exceptional situation.

Nice to Have

• Experience in the life/health science industry, notably pharma
• Experience in containerization, Kubernetes, and relevant distributed computing for training and inference
• Experience with NoSQL databases
• Familiarity with architectural choices, particularly for ML systems
• Leadership skills and a solid network to help in hiring and growing the team

Perks & Benefits

• Work anywhere
• Personal development budget
• Annual budget to donate to the non-profit of your choice
• Health & wellness programs
• Life insurance

Veeva’s headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world.

Veeva is committed to fostering a culture of inclusion and growing a diverse workforce. Diversity makes us stronger. It comes in many forms. Gender, race, ethnicity, religion, politics, sexual orientation, age, disability and life experience shape us all into unique individuals. We value people for the individuals they are and the contributions they can bring to our teams.