Lingaro - ML/AI Engineer
Requirements
• 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 • 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 • 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.
Responsibilities
• 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
Benefits
• 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, depending on your location. • 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. • Internal Gallup Certified Strengths Coach to support your growth. • 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. Purchased for you or available to borrow, depending on your location.
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