ML/AI Engineer - GCP, Azure

Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.

The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team.

• →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

• 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. 

• 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.