Senior AI/ML Engineer

The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team.   Tasks:   • Working with Data Science teams to implement Machine Learning models into production  • Design, delivery GenAI solutions   • Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency  • Design, delivery and management of industrialized processing pipelines  • Defining and implementing best practices in ML models life cycle and ML operations/LLM operations  • Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices  • Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations  • Gathering technical requirements & estimating planned work  • Presenting solutions, concepts and results to internal and external clients  • Creating technical documentation   What We're Looking For:   • At least 5+ years of Data engineering experience with last 3 years experience in building Data processing   • At least 5+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)  • At least 3+ years of experience in production-ready ML-related code development  • At least 1+ years of experience with GenAI (ChatGPT, Gemini, RAGs, prompt engineering) • Practical experience in MLOps/LLMOps tools like AzureML/AzureAI  • Practical experience with Databricks  • Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures  • Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP  • Experience in at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps  • Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar  • Experience in designing and implementing data pipelines  • Good communication skills  • Ability to work in a team and support others  • Taking responsibility for tasks and deliverables  • Great problem-solving skills and critical thinking  • Fluency in written and spoken English.    What Will Set You Apart:   • Experience in designing, programming ML algorithms, and data processing pipelines using Python  • Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps)  • Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes. Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.     We offer:   • Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites. • “Office as an option” model. You can choose to work remotely or in the office.   • Workation. Enjoy working from inspiring locations in line with our workation policy.  • Great Place to Work® certified employer. • Flexibility regarding working hours and your preferred form of contract.   • Comprehensive online onboarding program with a “Buddy” from day 1.    • Cooperation with top-tier engineers and experts.   • Unlimited access to the Udemy learning platform from day 1. • Certificate training programs. Lingarians earn 500+ technology certificates yearly.  • Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. • Grow as we grow as a company. 76% of our managers are internal promotions.   • A diverse, inclusive, and values-driven community.    • Autonomy to choose the way you work. We trust your ideas.   • Create our community together. Refer your friends to receive bonuses.   • Activities to support your well-being and health. • Plenty of opportunities to donate to charities and support the environment.   • Modern office equipment. Purchased for you or available to borrow, depending on your location.