Senior Machine Learning Engineer

Cognizant Romania is home to 2400+ creative technologists and is one of Eastern Europe's largest Software Product Engineering delivery networks. We serve global clients in several industries, including Banking & Financial Services, Insurance, Healthcare & Life Sciences, Communication Media & Technology, and Retail & MLEU (manufacturing, logistics, energy & utilities).

Cognizant Romania was established in 2018 when Cognizant acquired Softvision, a company founded in the late 1990s in Cluj-Napoca, Romania. We continue to build on our history as the preferred engineering partner for thriving Silicon Valley tech companies, now as a prominent Cognizant next generation studio.

About the role:

While we welcome applications from across Romania, this role is primarily intended for candidates based in Cluj-Napoca and Bucharest , to support team collaboration, project activities and onsite engagement when required. We also encourage applications from professionals located in Iași and Timișoara .

• Design, develop, and deploy machine learning models and pipelines end-to-end, from prototyping through production release.
• Build and maintain APIs and microservices using FastAPI to serve models and integrate them into client systems.
• Architect and implement RAG systems, including document ingestion, embedding pipelines, vector stores, and LLM orchestration.
• Apply classical ML techniques (regression, classification, clustering, time series, ensemble methods) where they are the right tool for the job — not every problem needs a foundation model.
• Own the full ML lifecycle: data exploration, feature engineering, model training, evaluation, deployment, monitoring, and iteration.
• Collaborate with cross-functional teams including data engineers, backend developers, product managers, and client stakeholders.
• Contribute to and uphold mature engineering practices: code reviews, CI/CD pipelines, automated testing, versioned releases, and documentation.
• Design and maintain data pipelines for model training and inference, including extraction from relational databases, data transformation, and loading into feature stores or serving layers.

What We're Looking For

• Strong proficiency in Python and its ML ecosystem (scikit-learn, pandas, NumPy, XGBoost/LightGBM, PyTorch or TensorFlow).
• AWS knowledge in various similar projects
• Solid experience with Git-based workflows, branching strategies, and collaborative development practices.
• Hands-on experience building REST APIs with FastAPI (or equivalent frameworks), including async patterns, dependency injection, Server-Side Events, and request validation.
• Practical knowledge of RAG architectures: embedding models, vector databases, chunking strategies, prompt engineering, and LLM integration.
• Familiarity with MLOps tools and practices: experiment tracking (MLflow, Weights & Biases), model registries, containerization (Docker), and CI/CD for ML (GitHub Actions, GitLab CI, or similar).
• Understanding of release management processes: semantic versioning, staged rollouts, rollback strategies, and environment promotion (dev → staging → production).
• Proficient in SQL and comfortable working with relational databases; able to write performant queries for data extraction, validation, and analysis.
• Familiarity with Change Data Capture (CDC) patterns and tools (e.g. database triggers, log-based replication) for building reactive, event-driven data flows.
• Solid understanding of idempotency in data and ML pipelines — designing processes that can be safely retried or re-run without producing duplicates or side effects.
• Strong communication skills — you can explain a model's behavior to a non-technical audience and write documentation that your future self will thank you for.

Cognizant Romania Employee Benefits:

• Flexible Work Schedule – Outside of core working hours, you have the flexibility to arrange your schedule in a way that best suits your personal and professional needs.
• Flexible Hybrid Approach – We support a hybrid working model that helps you balance remote and office work. Employees based near a Cognizant office are expected to spend a minimum of 4 days per month onsite.
• Annual Leave – Enjoy 26 vacation days each year to relax, recharge, travel, and spend quality time with family and friends.
• Learning & Development – Access a wide range of training programs, workshops, certifications, and continuous learning opportunities to support your professional growth.
• Private Medical Insurance – Comprehensive healthcare coverage for your wellbeing and peace of mind.
• Employee Assistance Program (EAP) – Confidential professional support services to help you navigate personal, emotional, financial, legal, or work-related challenges.
• Meal Tickets – Monthly meal allowance provided through meal vouchers.
• Referral Bonus Program – Help us grow our team and be rewarded for successful referrals.
• Life Insurance – Additional protection and financial security
• Banking Benefits – Preferential banking services and financial products through our partner institutions.
• Bookster Library – Access thousands of books, audiobooks, and learning resources to support both personal and professional development.

Please note that only suitable candidates will be contacted. Cognizant and its affiliated companies are firmly committed to protecting your privacy. This Candidate Privacy Notice provides you with all the details on what we do with Personal Information we collect during and after the recruitment process.