AI/ML Data Engineer

Job Description

AI/ML Data Engineer

The AI/ML Data Engineer builds and maintains the production pipelines that turn unstructured text and documents into reliable, model-ready data for our team's Generative AI and Natural Language Processing (NLP) applications and services. Key focus areas will include engineering data products built from licensed scientific literature, patents, clinical trials, and more. You'll develop ingestion and parsing pipelines for unstructured or semi-structured text data, with data-quality checks built in. These data products support critical use cases spanning early-stage scientific research to post-market surveillance, including systematic literature reviews, competitive intelligence, target identification, and safety monitoring. 

You'll be mentored by senior engineers and work directly alongside the data scientists and scientific subject matter experts who use your data. You'll gain hands-on exposure to how data feeds ML and large language model (LLM) systems, see your work accelerate research, and ultimately help bring therapeutics to patients. As you grow, you'll have opportunities to expand your skills in advanced pipeline performance tuning and lakehouse data modeling. The position is embedded within a cross-disciplinary team of data scientists, bioinformaticians, and engineers dedicated to using cutting-edge AI/ML and data science techniques to drive drug discovery and development. 

What you will do:

• Pipeline delivery: Build and maintain production data pipelines, transformations, and automated workflows that turn scientific text into data products 

• Requirements validation: Clarify the requirements for your tasks, proactively identify gaps and assumptions, and raise questions before and during implementation 

• Engineering standards: Adopt and contribute to the team's data engineering practices, propose schemas that fit the team's data standards, and actively participate in constructive code reviews 

• Data quality and reliability: Build automated schema, completeness, and constraint checks into pipelines, and create test datasets for integration and regression testing 

• Pipeline maintenance: Monitor pipelines, troubleshoot operational failures, apply dependency and platform upgrades, and keep data products reliable and cost-efficient 

• ML productionization: Support the deployment of ML pipelines into production 

• AI-assisted engineering: Use coding agents in your daily development and contribute to the team's agent-assisted workflows, such as pipeline-failure triage 

What you should have

• 3+ years of professional experience in data engineering or a closely related area 

• 2+ years of experience building data pipelines using Python and SQL 

• A Bachelor's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience 

What we offer:

• Exciting work in a great team, global projects, international environment
• Opportunity to learn and grow professionally within the company globally
• Hybrid working model, flexible role pattern
• Competitive salary & incentive pay
• Pension and health insurance contributions
• Internal reward system and referral scheme
• 5  weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40  paid hours annually for volunteering activities, 12 weeks of parental contribution
• Cafeteria for tax free benefits according to your choice (meal vouchers, sport, culture, health, travel, etc.), Multisport Card
• Vodafone, Raiffeisen Bank, Foodora, and discount programs
• Up-to-date laptop and iPhone
• Parking in the garage, showers, refreshments, massage chairs, library, music corner

Additional job details

In addition to building and maintaining our suite of tools, our team consults on how software capabilities, data products, and AI/ML can support the projects of our 5,000+ stakeholders (scientists, engineers, regulatory liaisons, data scientists, etc.) across our multi-national organization. We strive to enhance data science, NLP, and AI literacy across these groups. 

As part of our work, our team has opportunities to coauthor internal and external presentations, white papers, manuscripts, and/or open-source code releases. We invest in your professional growth by providing access to specialized learning platforms, opportunities to attend industry conferences, participation in internal communities of practice, and the chance to learn the science of drug discovery and development directly from domain experts. 

Additional location(s) Compensation Information:

Required Skills:

Data Engineering, Data Standards, Data Storage, Design Applications, Engineering Standards, Generative AI, Git, GitHub, GitHub Actions, Machine Learning (ML), Python (Programming Language), Software Development, Testing

Preferred Skills:

Current Employees apply HERE

Current Contingent Workers apply HERE

Search Firm Representatives Please Read Carefully 
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation:

VISA Sponsorship:

Travel Requirements:

Flexible Work Arrangements:

Hybrid

Shift:

Valid Driving License:

Hazardous Material(s):

Job Posting End Date:

11/24/2026

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.