About vacancy:

We are looking for a Senior Computer Vision Engineer who will become the technical driving force behind production-grade CV systems for a rapidly growing retail analytics and fraud prevention platform. You will work directly with a US-based client (New York) and join a team of 30+ engineers, QA specialists, and managers. This is a role for an experienced engineer who can confidently move from training custom YOLO architectures to deploying highly optimized models on edge devices, while also contributing to multimodal innovations involving LLMs. The team is very easy-going, supportive, and fun — and the product is scaling extremely fast.

Qualifications:

5+ years of hands-on computer vision engineering, with a proven track record of shipping models to production;

Deep expertise with YOLO and YOLO-E architectures - you’ve trained them, tuned them, and know their quirks intimately;

Edge deployment mastery - experience with TensorRT, ONNX Runtime, or similar frameworks for optimizing models for constrained devices;

LLM and LLMOps experience - practical knowledge of large language models, fine-tuning, prompt engineering, and building reliable LLM-powered systems;

Strong software engineering fundamentals - clean code, version control, CI/CD for ML, and the ability to build maintainable systems;

Production ML experience - you understand the difference between a Jupyter notebook and a production-grade ML system.

Will be a plus: Experience with retail, inventory management, or similar product-focused CV applications; Background with PyTorch and modern training frameworks; Familiarity with synthetic data generation and data augmentation techniques; Knowledge of model versioning, experiment tracking (MLflow, Weights & Biases, etc.); Publications or open-source contributions in computer vision; Experience with AWS (EC2, ECS, Fargate, S3, Bedrock, Sagemaker, etc.)

Project description:

The project focuses on building real-world retail computer vision solutions used in production across numerous customer locations. You will work on object detection, inventory tracking, fraud prevention, and product recognition. Models are deployed on edge devices and must be optimized for constrained hardware.

Tech Stack: PyTorch, YOLO variants, TensorRT, ONNX, Docker, Kubernetes, MLOps tooling.

Interview stages: Prescreen Call with Recruiter; Client Interview – Culture Fit; Client Interview – Final Technical.

Responsibilities:

Model Development: Design, train, and iterate on custom object detection models specifically tuned for retail environments, inventory tracking, and product recognition.

Edge Optimization: Take state-of-the-art models and make them blazingly fast for edge deployment through quantization, pruning, and architectural optimization.

Dataset Engineering: Build robust data pipelines and annotation workflows to continuously improve model performance on diverse retail scenarios.

Research & Innovation: Stay ahead of the curve on CV research, prototype new architectures, and determine what’s actually production-ready versus academic noise.

Technical Leadership: Mentor engineers, establish best practices for model development, and drive technical decisions around our CV infrastructure.

LLM Integration: Explore and implement multimodal approaches combining vision and language models for enhanced product understanding and classification.

Typical tasks for 3-6 months: You’ll be the technical force behind our computer vision capabilities, building and optimizing models that power real-world retail applications. This role demands someone who can move seamlessly from training custom YOLO architectures to deploying optimized models on edge devices, all while pushing the boundaries of what’s possible in retail computer vision.

We offer:

Career and professional development opportunities;

Flexible working hours;

Remote work opportunities;

20 paid vacations per business year and National Ukrainian holidays;

10 paid sick leaves;

Mentorship program;

Courses and Certifications;

Business English courses of all levels;

Team parties, company events, and branded presents.

Alina

Recruiter