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AI Product Engineer at Weekday. Location Information: India - Remote. . This role is for one of Weekday’s clients. Salary range: Rs 2000000 - Rs 9000000 (ie INR 20-90 LPA). Min Experience: 4 years. JobType: full-time. Requirements. What You’ll Do. ● 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 domain. What 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. . Who You Are. ● You’ve built systems — not just prototypes. ● You care about both ML results and the system’s behavior in production. ● You’re comfortable taking a rough business goal and shaping the technical path to get there. ● You’re energized by product-focused AI work — things that users feel and rely on. ● You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful. What You Get. ● Full autonomy over your problem space. ● A builder-first, no-handoff culture. ● Remote-first flexibility (India preferred). ● Base + Variable + meaningful equity. ● A product shipping to some of the world’s most recognizable brands. .