ml engineer for renewable energy asset monitoring
1 month ago
Barcelona
Описание: DNV is an independent expert in assurance and risk management. Its Energy Systems division helps customers navigate the transition to a decarbonized and sustainable energy future by assuring that energy systems operate safely and effectively through increasingly digital solutions. Digital and Data Solutions develops software and data-driven solutions for challenges in energy, infrastructure, and sustainability. • Design and implement a scalable architecture for role-based AI agents supporting asset management, asset ownership, O&M, predictive maintenance, trading, and analytical workflows;, • Define agent responsibilities, tools, interaction patterns, task delegation, context sharing, and hand-offs between specialised agents;, • Integrate agents with Horizon data sources, including operational time-series data, alarms, events, asset metadata, analytical results, forecasts, reports, logbooks, and technical documentation;, • Build evaluation frameworks and representative test datasets covering answer quality, groundedness, tool selection, workflow completion, hallucination risk, safety, regression, latency, and operational reliability;, • Implement observability and traceability across agent execution, including prompts, retrieved context, tool calls, model responses, decisions, failures, and user feedback;, • Deploy and operate AI services in production with software and platform engineers;, • Collaborate with renewable energy domain experts to ensure agent outputs are technically meaningful, evidence-based, and appropriate for operational decision-making;, • Stay informed about developments in LLMs, agent orchestration, multimodal systems, evaluation, and AI engineering, and assess them for production use., • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, or a related field, or equivalent practical experience;, • Proven experience building AI agents, agentic workflows, or AI assistants, preferably in production environments;, • Experience with Retrieval-Augmented Generation (RAG), embeddings, vector search, and prompt engineering;, • Strong Python software engineering skills and experience developing production-grade applications;, • Experience integrating AI solutions with APIs, databases, and enterprise systems;, • Familiarity with Git, CI/CD, Docker, and cloud-native development practices;, • Strong communication skills and fluency in written and spoken English;, • Curiosity, adaptability, and proactive collaboration in fast-moving environments;, • Ownership of projects and ability to communicate complex AI concepts clearly to technical and non-technical stakeholders;, • A short report or demo of an AI agent built by the candidate is required as part of the interview process;, • Final candidates must undergo background checks in accordance with applicable country-specific laws and practices;, • Nice to have: experience deploying AI workloads on Kubernetes, experience with self-hosted LLMs and model serving, familiarity with ClickHouse, MongoDB, vector databases, and time-series data platforms., • Medical Scheme;, • Commuting Allowance;, • Life Insurance;, • Pension Plan;, • Kindergarten Allowance;, • 40 Hours per week with a flexible schedule;, • Home working allowance 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. #J-18808-Ljbffr