- Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, AI architectures.
- Practical experience in Databricks.
- Practical experience in MLOps tools like MLFlow, Azure ML, GCP Vertex, AWS Sagemaker.
- 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.
- Good understanding of GenerativeAI and Large Language Models tech stack and concepts (OpenAI, LLM orchestrators – Langchain, Semantic Kernel, etc.) is a plus.
- Stable employment. On the market since 2008, 1300+ 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.
,[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. ] Requirements: Python, AI, Databricks, Azure ML, Azure, Spark, MLOps, Scala Tools: Agile. Additionally: Sport subscription, Private healthcare, International projects, Free coffee, Modern office, No dress code, In-house trainings.
GitLab LangChain OpenAI GenAI CI/CD Artificial intelligence (AI) Python Apache Spark GitHub Actions azureml Semantic core DevOps Docker MLflow Kubernetes Azure DevOps Machine Learning Amazon SageMaker LLM