{"id":4024120,"url":"https://alion.io/job/merck-co-aiml-data-engineer","title":"AI/ML Data Engineer","company":{"id":3768,"name":"Merck & Co.","domain":"msd.com","url":"https://alion.io/company/msd","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":97,"open_postings":192,"ghost_share":0.031,"stale_share":0.156,"repost_share":0.177,"time_to_fill_p50_days":16,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Prague, Czech Republic"],"countries":["CZ"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-10T16:17:00Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T16:17:00Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Description\nAI/ML Data Engineer\nThe 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.\nYou'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.\nWhat you will do:\nPipeline delivery: Build and maintain production data pipelines, transformations, and automated workflows that turn scientific text into data products \nRequirements validation: Clarify the requirements for your tasks, proactively identify gaps and assumptions, and raise questions before and during implementation \nEngineering 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 \nData quality and reliability: Build automated schema, completeness, and constraint checks into pipelines, and create test datasets for integration and regression testing \nPipeline maintenance: Monitor pipelines, troubleshoot operational failures, apply dependency and platform upgrades, and keep data products reliable and cost-efficient \nML productionization: Support the deployment of ML pipelines into production \nAI-assisted engineering: Use coding agents in your daily development and contribute to the team's agent-assisted workflows, such as pipeline-failure triage \nWhat you should have\n3+ years of professional experience in data engineering or a closely related area \n2+ years of experience building data pipelines using Python and SQL \nA Bachelor's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience \n What we offer:\nExciting work in a great team, global projects, international environment\nOpportunity to learn and grow professionally within the company globally\nHybrid working model, flexible role pattern\nCompetitive salary & incentive pay\nPension and health insurance contributions\nInternal reward system and referral scheme\n5 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\nCafeteria for tax free benefits according to your choice (meal vouchers, sport, culture, health, travel, etc.), Multisport Card\nVodafone, Raiffeisen Bank, Foodora, and discount programs\nUp-to-date laptop and iPhone\nParking in the garage, showers, refreshments, massage chairs, library, music corner\n\nAdditional job details\nIn 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.\nAs 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.\nAdditional location(s) Compensation Information:\nRequired Skills:\nData Engineering, Data Standards, Data Storage, Design Applications, Engineering Standards, Generative AI, Git, GitHub, GitHub Actions, Machine Learning (ML), Python (Programming Language), Software Development, TestingPreferred Skills:\nCurrent Employees apply HERE\nCurrent Contingent Workers apply HERE\nSearch Firm Representatives Please Read Carefully\nMerck & 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.\nEmployee Status:\nRegularRelocation:\nVISA Sponsorship:\nTravel Requirements:\nFlexible Work Arrangements:\nHybridShift:\nValid Driving License:\nHazardous Material(s):\nJob Posting End Date:\n11/24/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. 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