HERE Technologies

Bengaluru
Total Offices: 4
6,000 Total Employees
Year Founded: 1985

HERE Technologies Offices

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 2 days a week

Global Office Locations

Bengaluru

RMZ Eco Space, Unit No- 501 Campus 1C, 5th Floor Sarjapur Outer Ring Road, Bengaluru, India, 560103

Gurugram

22nd Floor, DLF Epitome, Building No 5, Tower A, DLF Cyber City Phase 2, Sector 25, Gurugram, India, 122002

Mumbai

11th Floor, B Wing, Nesco IT Park - Tower 4 Western Express Highway, Mumbai, India, 400063

Navi Mumbai

Unit No. 901, 9th Floor, Building No. 4, M/S Gigaplex Estate Private Limited-SEZ, Navi Mumbai, India, 400708

3 Hours AgoSaved
Hybrid
Mumbai, Maharashtra, IND
Artificial Intelligence • Automotive • Computer Vision • Information Technology • Internet of Things • Logistics • Software
Design and build scalable systems, data pipelines, and full‑stack applications to validate product quality and produce KPI reporting. Integrate AI-driven features (RAG, agents, semantic search), automate statistical analysis, support CI/CD, conduct code reviews, and collaborate in Agile teams to translate business needs into technical solutions.
2 Days AgoSaved
Hybrid
Navi Mumbai, Thane, Maharashtra, IND
Artificial Intelligence • Automotive • Computer Vision • Information Technology • Internet of Things • Logistics • Software
Serve as primary technical advisor for strategic customers, troubleshoot and resolve complex SDK/platform issues, lead root-cause analysis, drive cross-functional solutions with product and engineering, support implementations and RFQs, conduct training, and improve support processes and product usability.
2 Days AgoSaved
Hybrid
Mumbai, Maharashtra, IND
Artificial Intelligence • Automotive • Computer Vision • Information Technology • Internet of Things • Logistics • Software
Lead development of large-scale vision foundation and multimodal AI models for image and video understanding. Design, train, optimize, and deploy ViT-based and VLM systems, build RAG and retrieval pipelines, manage large multimodal datasets, optimize distributed training and GPU workflows, and translate research into production-ready solutions while evaluating model robustness and retrieval effectiveness.