HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely. At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel. About Team: You will join the Technology Innovation Lab, a cross-disciplinary team focused on advancing AI-powered capabilities across HERE. Within the Mapmaking AI initiative, the Context Engineering workstream develops intelligent systems that combine machine learning, foundation models, agentic AI, and geospatial intelligence to transform proven concepts into scalable production solutions. The team collaborates closely across engineering, research, and product functions to deliver innovative AI solutions that drive business impact. We are looking for a Lead ML & AI Engineer to define and deliver the next generation of AI-powered platforms and intelligent automation solutions at HERE. In this role, you will provide technical leadership across machine learning, generative AI, agentic AI, multimodal systems, and representation learning initiatives. You will collaborate closely with engineering leaders, researchers, and product teams to architect scalable, production-ready AI solutions that solve complex spatial, operational, and knowledge-driven challenges. Key Responsibilities • Lead the design and implementation of representation learning systems, embedding models, vector search solutions, and retrieval-augmented architectures. • Define technical architecture for AI-first platforms utilizing foundation models, large language models, autonomous agents, and classical machine learning techniques. • Establish best practices for agentic AI systems including orchestration, memory management, tool integration, confidence calibration, and human-in-the-loop workflows. • Architect multimodal AI solutions that combine imagery, text, and structured data for detection, classification, reasoning, and decision support. • Evaluate emerging AI technologies and guide adoption decisions across the organization. • Translate complex business and technical challenges into scalable, explainable, responsible AI solutions. • Define success metrics and partner with leadership to ensure measurable business impact. • Mentor engineers and data scientists, helping elevate technical excellence across the team. • Contribute to innovation through intellectual property development, research publications, and technical thought leadership. Who you are Master's degree or Ph.D. in Computer Science, AI/ML, Mathematics, or a related field. • Candidates with a Master's should have 8–10+ years of experience, including demonstrated technical leadership. • Ph.D. holders may have 6–8+ years of relevant experience, including demonstrated technical leadership. • Proven track record of leading the design and delivery of production ML systems end to end, and setting technical direction that other engineers build on. • Deep expertise in representation learning and embeddings, vector similarity search, and retrieval-augmented approaches — able to architect the foundation-model core, not just contribute to it. • Strong command of ML fundamentals, including regression, classification, forecasting, and model interpretability. • Hands-on experience with deep learning architectures such as CNN, LSTM, GRU, GANs, BERT, Diffusion Models, and Transformers. • Substantial experience with LLMs (e.g., GPT-3/4, Claude, Mistral) and architecting agent-based solutions using frameworks like LangGraph, CrewAI, or AutoGen. • Multimodal / vision-language model experience — jointly encoding imagery with text or structured data — at an architectural level. • Proficiency in Python; familiarity with other programming languages like C++ or Java is a plus. • Fluency with ML frameworks such as PyTorch, TensorFlow, scikit-learn, and experience working with large datasets and distributed systems. • Experience with geospatial or spatial data — spatial indexing, geospatial data structures, or entity resolution / conflation — is a strong advantage, as the work centers on spatial reasoning at scale. • A track record of making independent architectural decisions, defending them with evidence, and holding a high measurement bar for whether systems actually work. • Demonstrated ability to mentor senior engineers and lead cross-functional, agile teams. • Curiosity and exposure to adjacent technologies like TinyML, Quantum Computing, or 3D modeling/AR is an advantage. • Excellent problem-solving and communication skills, including the ability to represent complex technical work to senior stakeholders. HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.
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