Sr. Engineer @Linger in Lingaro

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. 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, GCP Vertex, AWS Sagemaker 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. 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, GCP, MLOps, Spark, Scala Tools: . Additionally: Sport subscription, Small teams, International projects, Private healthcare, Free coffee, In-house trainings, Modern office, No dress code.