ML Engineering Adoption Champion at Merck Sharp & Dohme Corp. /Netherlands

, , Czechia -

Full Time

Start Date

Immediate

Expiry Date

31 Jan, 26

Salary

0.0

Posted On

02 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, ML Frameworks, Databricks Ecosystem, MLOps Practices, DevOps, Cloud Computing, Data Science, Machine Learning Engineering, Communication Skills, Data Governance, Containerization, Monitoring Solutions, Package Development, Multi-language Proficiency, Technical Reviews, Architectural Decisions

Industry

Pharmaceutical Manufacturing

Description

Job Description The Position We are seeking a ML Engineering Adoption Champion to join Our Company. This is a permanent position. What will you do? Lead ML platform initiatives from conception to deployment, making autonomous technical decisions that shape our customer usage patterns. Champion ML platform adoption across teams, serving as the go-to expert and advocate for best practices. Design and implement scalable AI ML tools and workflows that support diverse scientific use cases. Drive architectural decisions and execute strategic AI, ML, and Data & Analytics roadmap initiatives. Co-Develop reusable templates, notebooks, and reference architectures showcasing platform best practices. Conduct technical reviews of customer implementations to ensure quality and optimization. Deliver hands-on technical workshops and create learning materials to build customer capabilities. Gather structured user feedback to inform product development priorities. Create compelling demonstrations highlighting platform capabilities in real-world contexts. Help organizations measure adoption success and navigate the organizational challenges of implementing ML solutions. Qualifications, Skills & Experience Required Advanced proficiency in Python including ML frameworks (scikit-learn, TensorFlow, PyTorch) Extensive hands-on experience with Databricks ecosystem (Delta Lake, MLflow) Strong knowledge of MLOps practices for AI/ML model lifecycle and governance DevOps foundation with Git, and CI/CD Cloud computing experience within data & analytics domain (AWS, Databricks, Dataiku or similar) 5+ years of experience in data science or machine learning engineering roles Excellent communication skills with ability to explain complex concepts to various audiences Bachelor's degree in Computer Science, Statistics, or related field; advanced degree preferred Nice to have Experience with Databricks, Domino, Dataiku or dbt platforms Experience with LLM and Foundational models Monitoring solutions (Grafana, Data observability tools) Package development and artifact management Multi-language proficiency (R, Shell, Python) Familiarity with containerization (Docker, Kubernetes) for ML workloads Background in a specific industry vertical (healthcare etc.) Knowledge of data governance and ML compliance frameworks 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 (e.g., even 80% full-time is possible in justified cases) Pension and health insurance contributions Internal reward system plus referral programme 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, Lítačka, sport, culture, health, travel, etc.), Multisport Card Vodafone, Raiffeisen Bank and Foodora discount programmes Up-to-date laptop and iPhone Parking in the garage, showers, refreshments, massage chairs, library, music corner Competitive salary, incentive pay, and many more Ready to take up the challenge? Apply now! Know anybody who might be interested? Refer this job! Required Skills: Business Intelligence (BI), Business Intelligence (BI), Computer Science, Containerization, Customer Implementations, Database Administration, Databricks Platform, Databricks Unified Data Analytics Platform, Data Engineering, Data Governance, Data Management, Data Modeling, Data Visualization, Design Applications, Information Management, Kubernetes, Language Assessments, Machine Learning, Machine Learning Operations, Product Development, Quality Assurance (QA), Quality Control Management, Quality Management, Social Collaboration, Software Development {+ 1 more} 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: 11/17/2025 *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. Our company is a global health care leader with a diversified portfolio of prescription medicines, vaccines and animal health products. The difference between potential and achievement lies in the spark that fuels innovation and inventiveness; this is the space where we have codified our legacy for over a century. Our success is backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.

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Responsibilities

Lead ML platform initiatives from conception to deployment and champion ML platform adoption across teams. Design and implement scalable AI ML tools and workflows while conducting technical reviews to ensure quality and optimization.