Data Scientist

HERE Technologies · Mumbai

  • Experience6–7 yrs
  • SalaryDisclosed
  • RoleAI Engineer
  • Work modeonsite
  • Posted14 Oct 2026

About HERE Technologies

HERE Technologies is hiring in Mumbai in technology software. This role looks for around 6+ years of experience.

Skills

  • Python
  • PyTorch
  • TensorFlow
  • Large Language Models (LLMs)
  • Generative AI
  • Agentic AI
  • LangGraph
  • CrewAI
  • AutoGen
  • representation learning
  • vector similarity search
  • retrieval-augmented generation
  • deep learning
  • MLOps

The role

Builds AI and machine learning systems for a technology company working on spatial challenges. Develops Generative AI, agentic systems, retrieval layers and multimodal models using Python, PyTorch and TensorFlow. Applies representation learning and vector similarity search to production systems.

Full job description

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.Support and mentor engineers and data scientists in best practices for prompt design, agent workflows, evaluation frameworks, and research translation.Contribute to HERE's innovation footprint through patents, internal IP development, and peer-reviewed publications.Qualifications6+ years in ML/AI engineering, with a track record of shipping production systems (not solely research prototypes).Strong foundation in representation learning and embeddings, vector similarity search, and retrieval-augmented approaches.Proven experience building and deploying deep learning models at scale, including data pipelines, evaluation, and MLOps practices.Hands-on experience with LLMs and modern transformer architectures.Proficiency in Python and modern ML frameworks (PyTorch and/or TensorFlow).Ability to own ambiguous, end-to-end problems and make independent architectural decisions.