AI Product Engineer - Visual Intelligence & Automation

Must have skills required:

Our engineers dont just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges this role is for you. Youll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale.

What Youll 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 youll 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 Youll 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 theyre 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

Youve built systems not just prototypes

You care about both ML results and the systems behavior in production

Youre comfortable taking a rough business goal and shaping the technical path to get there

Youre energized by product-focused AI work things that users feel and rely on

Youve worked in or want to work in a startup-grade environment: messy, fast, and impactful