Lead Engineer - AI
- India
- Permanent
- Full-time
Salary range: Rs 4000000 - Rs 7000000 (ie INR 40-70 LPA)
Min Experience: 5 years
Location: Remote (India)
JobType: full-timeRequirementsWhat You’ll Do● 4-7 Years of full time experience, Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills● Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines.● Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch.● Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision.● Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput● Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it● Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domainWhat You’ll Need● 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions)● Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques.● 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines● Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing.● Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement.● Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks.● Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc.● Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda).● Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing.● A customer-centric approach — you think about how your work affects end users and product experience, not just model performance● A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed● The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket