ML/AI Engineer

Responsibilities:

• Building high-performing, scalable, enterprise-grade ML/AI applications in cloud environment.
• Working with Data Science teams to implement Machine Learning and statistical models into production.
• Practical and innovative implementations of 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.
• Implementing AI/MLOps 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.

Expectations:

• At least 5 years of experience in a similar position.
• Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, AI architectures.
• Practical experience in MLOps tools like MLFlow, Azure ML and/or Databricks.
• Good understanding of Cloud concepts and architectures as well as working knowledge with selected cloud services, preferably MS Azure.
• Strong experience in at least one of the following domains: Machine Learning, Deep Learning, Data Science, MLOps, GenerativeAI.
• Experience in programming ML algorithms and data processing pipelines using Python.
• At least 2 years of experience in production ready code development.
• Practical skills with scripting languages.
• 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.
• Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab or Azure DevOps) is a plus.
• Experience productization ML solutions using technologies like Spark/Databricks or Docker/Kubernetes is a plus.

What 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.
• 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+trainings, 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.