Lead ML & AI Engineer

Responsibilities

In this role you will build the core AI building blocks models, agents, and retrieval components that domain teams consume rather than rebuild, and provides hands-on technical leadership for the engineers building alongside them. In addition you will:

Build Core AI Components

• Own end-to-end delivery of core building blocks  e.g., the representation-retrieval critical path (embeddings, similarity search, semantics) that other domain teams call into.
• Take architectural direction from the Principal/Lead Engineer and turn it into a working, production-ready component — not just a prototype.

Technical Leadership Without Full Architectural Ownership

• Provide day-to-day technical leadership for AI/ML Engineer II and Geo AI Engineer II team members working on related components.
• Make implementation-level technical calls independently; escalate genuine architectural questions to the Principal/Lead rather than deciding them ad hoc.

Bridging Architecture and Execution

• Translate the Principal/Lead's architectural decisions into concrete technical specs the rest of the team can build against.
• Flag early when a building block being built won't actually generalize across domain teams, before it ships.

Qualifications

You are a fast learner, with an eye for detail, strong problem-solving and debugging skills, and a passion for applying AI to complex engineering problems. In addition you have the following qualifications:

• Bachelor’s, Master’s degree or PHD in Computer Science, AI/ML, Mathematics, or a related quantitative field.
• Candidates with a Bachelor’s or Master's should have 7+ years of experience, including demonstrated technical leadership.
• Ph.D. holders may have 6+ 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.
• 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.

What we offer

HERE offers an opportunity to work in a cutting-edge technology environment with challenging problems to solve! You can make a direct impact on delivery of company´s strategic goals and the freedom to decide how to perform your work. We will support you in delivering your day-to-day tasks and achieving your personal goals and developing your skills. Personal development is highly encouraged at HERE. You can take different courses and training at our online Learning Campus and join cross-functional team projects within our Talent Platform.

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.