Sr ML & AI Engineer

What's the role?

As a Senior ML & AI Engineer, you will help shape the next generation of AI-powered products and platforms at HERE. You will design, develop, and deploy intelligent systems that combine Generative AI, Agentic AI, machine learning, and advanced retrieval techniques to solve complex business and spatial challenges. You will have the opportunity to:

• Architect and build AI-first systems using Large Language Models (LLMs), autonomous multi-agent architectures, and classical ML models such as regression, clustering, XGBoost, SVM, and tree-based learners.

• Build the representation and retrieval layers that power intelligent systems — designing embedding models, unified latent-space representations across heterogeneous signals, vector similarity search, and retrieval-augmented approaches at scale.

• Lead the development of Agentic AI solutions — task orchestration, memory and context management, tool invocation, and human-agent collaboration — using frameworks such as LangGraph, CrewAI, and AutoGen.

• Design and deliver end-to-end Generative AI applications for text generation, summarization, code synthesis, image generation, and multi-modal interfaces, optimizing prompt engineering and model fine-tuning.

• Develop multimodal and vision-language systems that jointly encode imagery with text and structured attributes for detection, classification, and semantic reasoning.

• Apply deep learning techniques including CNNs, RNNs (LSTM, GRU), GANs, diffusion models, transformers, and graph neural networks to real-world tasks in vision, language, and planning.

• Design and calibrate confidence-gating and escalation logic for autonomous systems, including human-in-the-loop and active-learning workflows.

• Collaborate across teams to translate domain problems into scalable, explainable, and production-ready AI solutions, incorporating responsible AI principles.

• Stay at the forefront of AI research by evaluating and implementing emerging models, agentic frameworks, and open-source innovations, ensuring technical currency in a fast-evolving space.

• Design and lead experiments across advanced AI/ML areas including computer vision, NLP, and LLMs, and emerging domains such as distributed computing, 3D modeling, AR/VR, LiDAR/drone data processing, and quantum computing (good to have).

• Write efficient, production-quality code in Python, with working knowledge of C++ or Java where needed; leverage frameworks such as PyTorch, TensorFlow, and Spark for large-scale ML training and inference.

• Define and track KPIs at both individual and business-unit levels in partnership with the manager, ensuring impact-driven innovation.