ML/AI Engineer – GCP, Azure

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🕒 April 8

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Lingaro

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2008

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Lingaro is an end-to-end data services and analytics partner for global brands and enterprises, delivering data strategy, platform engineering, AI/ML (including generative AI), and data governance to unlock business value. It combines domain-focused analytics (supply chain, commercial/RGM, digital commerce, sustainability) with data platforms, visualization, MLOps, and secure cloud (Google Cloud) integrations, plus a creative arm (ALCHEMY) for data-driven brand and commerce experience design.

📋 Description

• 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

🎯 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 • Practical experience with Databricks • 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 • 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.

🏖️ 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.