Lead AI Engineer

Origin; Bengaluru; On-site; INR 9,066,183 - 12,692,656; Full time

Benefits offered by this job

Competitive salary

Equity

Flexible hybrid work

Job summary

A dynamic technology firm based in India seeks an experienced AI Research Engineer to innovate and develop cutting-edge systems utilizing deep-learning and vision-language models. This role involves researching generative models, architecting VLMs, and leading the development of auto-annotation pipelines. A strong background in deep-learning, coupled with a Ph.D. or extensive industry experience, is essential. Competitive compensation and a hybrid work environment are offered.

Qualifications

• 8+ years in deep-learning R&D or Ph.D./M.S. with a strong publication record.
• Demonstrated expertise in diffusion models and multimodal transformers.
• Strong mathematical foundation with ability to translate theory into production code.

Responsibilities

• Research diffusion-based generative models for wall-surface simulations.
• Architect and train Vision-Language Models and alignment objectives.
• Develop auto-annotation pipelines scalable to millions of frames.

Skills

Deep-learning R&D

Vision-Language Models

Python

PyTorch

Diffusion models

Education

Ph.D./M.S. in CS, EE, Robotics or related field

Tools

TensorRT

CUDA

JAX

Job description

As a core member of the AI Research team you'll turn cutting-edge, vision-language and diffusion advances into robust real-time systems that see reason and act on dynamic construction sites.

Key Responsibilities

• Research & innovate diffusion-based generative models for photorealistic wall-surface simulation, defect synthesis and domain adaptation.
• Architect and train Vision‑Language Models (VLMs) and Vision‑Language Alignment (VLA) objectives that connect textual work orders, CAD plans and sensor data to pixel‑level understanding.
• Lead development of auto‑annotation pipelines (active learning, self‑training, synthetic data) that scale to millions of frames and point‑clouds with minimal human effort.
• Optimize and compress models (INT8, LoRA, distillation) for deployment on Jetson‑class edge devices under ROS 2.
• Own the full lifecycle—problem definition, literature review, prototyping, offline/online evaluation and production hand‑off to perception & controls teams.
• Publish internal tech reports and external conference papers; mentor interns and junior engineers.

Qualifications & Skills

• 8+ years in deep‑learning R&D or Ph.D./M.S. in CS, EE, Robotics or related field with strong publication record.
• Demonstrated expertise in diffusion models (DDPM, LDM, ControlNet) and multimodal transformers / VLMs (CLIP, BLIP‑2, LLaVA, Flamingo).
• Proven success building large‑scale data‑centric AI workflows—active learning, pseudo‑labeling, weak supervision.
• Advanced proficiency in Python, PyTorch (or JAX), experiment tracking and scalable training (PyTorch Lightning, DeepSpeed, Ray).
• Familiarity with edge‑AI runtimes (TensorRT, ONNX Runtime), and CUDA / C++ performance tuning.
• Strong mathematical foundation (probability, information theory, optimization) and ability to translate theory into production code.
• Bonus: experience with synthetic data generation in Isaac Sim or robotics perception stacks (ROS2, Nav2, MoveIt 2, Open3D).

Why join us?

• Own breakthrough tech from idea to autonomous robot on active job‑sites—your work leaves the lab fast.
• Collaborate cross‑functionally with perception, controls, and product teams & publish at top venues with company support.
• Shape an industry by replacing dangerous, repetitive construction labor with intelligent robots.
• Competitive salary + equity, hardware budget, flexible hybrid work, and a culture that prizes deep work and rapid iteration.