Job Description

About Lingaro: Lingaro Group is the end-to-end data services partner to global brands and enterprises. We lead our clients through their data journey, from strategy through development to operations and adoption, helping them to realize the full value of their data. Our commitment to data excellence has created an environment that attracts the brightest global data talent to our team. We are a diverse team of 1300+ leading experts and talents excelling in the fields of data analytics, business intelligence , big data , data science & AI , digital commerce , and more from sites in Warsaw, Lublin, Zurich, Manila, Cincinnati, Singapore, Bengaluru, and Mexico City. As a value-driven company, we innovate with industry leaders in a friendly environment where know-how is shared, technical trainings are regularly scheduled, and professional growth is expected. It\'s that approach that gained us the Great Place to Work Certification. Join our values-driven community. Learn with can do attitude. Grow as you shape the data-driven world. Responsibilities: The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team. The key duties are: 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: 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. 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. Nice to have: Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab or Azure DevOps). Experience productization ML solutions using technologies like Spark/Databricks or Docker/Kubernetes. Good understanding of GenerativeAI and Large Language Models tech stack and concepts (OpenAI, LLM orchestrators - Langchain, Semantic Kernel, etc.).

foundit