Job description

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.

• Social fund benefits for everyone. All Lingarians can apply for social fund benefits, such as vacation co-financing.

• 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.