ML инженер

DNV is an independent expert in assurance and risk management. GreenPowerMonitor, a DNV company, uses data-driven digital solutions to optimize renewable energy installations and transform operational data into actionable insights for monitoring, optimization, and decision-making.

• Connect to diverse data sources within the Horizon platform and design Retrieval-Augmented Generation (RAG) pipelines for scalable AI systems;
• Extract, transform, and structure data for use with LLMs, manage embeddings, indexing, and context retrieval, and ensure AI models are grounded in accurate information;
• Design, deploy, fine-tune, and continuously improve production-grade LLM and multimodal agents;
• Optimize prompts, mitigate hallucinations, and evaluate model performance to deliver reliable, context-aware outputs;
• Build and maintain client-facing AI assistants and chatbots;
• Explain system behavior, capabilities, and limitations to technical and non-technical stakeholders;
• Integrate AI features into Horizon workflows;
• Stay up to date with advances in generative AI, agent-based systems, and instruction-tuned models;
• Experiment with frameworks like LangChain and collaborate on experiments using large instruction-tuned models;
• Collaborate with product and software teams to take AI solutions from concept to production;
• Ensure AI features are robust, scalable, and support Horizon users in monitoring, optimizing, and managing renewable energy assets.

• Master’s degree or equivalent experience in Mathematics, Data Science, Computer Science, Machine Learning, or a related field;
• Hands-on experience with Large Language Models (LLMs) or generative AI systems;
• Experience with RAG pipelines, embeddings, and prompt optimization;
• Strong understanding of Transformer architectures and fine-tuning;
• Proficiency in Python;
• Curiosity, adaptability, and a proactive approach;
• Ability to take ownership of projects;
• Ability to communicate complex AI concepts clearly to technical and non-technical stakeholders;
• Fluency in written and spoken English;
• Nice to have: familiarity with CI/CD, Docker, Kubernetes (K8s), and Git.

• Medical Scheme;
• Commuting Allowance;
• Life Insurance;
• Pension Plan;
• Kindergarten Allowance;
• 40 Hours per week with a flexible schedule;
• Friday home working allowance of up to 2 days per week;
• 23 Days of annual leave;
• Employee Referral scheme;
• Coaching, mentoring, international networks, individual competence development plans, and tailored training;
• Background checks will be conducted on all final candidates in accordance with applicable country-specific laws and practices.