About The Position:

We are looking for an experienced Senior Computer Vision Engineer (2-4 years experience) who has relevant experience in deep-learning, computer vision (CV), image processing, and machine learning. You will advance our next-generation field data capture and analysis platform. In this role, you will design and implement ML/CV models that extract intelligence from images, including shelf compliance, product recognition, and synthetic data generation for training and QA. You will work within a lean product engineering team, bridging R&D with production. You can expect to iterate quickly, incorporate customer feedback, and contribute across the stackfrom ML model training and deployment to integrating vision outputs into our web-based analytics dashboard. If you were waiting for the perfect opportunity to unleash your potential in AI, be part of a fun team to create immediate impact in solving real world problems, and have the credentials, we would love to hear from you!

Our client is a well funded AI company using breakthrough computer vision and machine learning technologies to solve some of the biggest opportunities in the retail sector. We are based out of the US / India, and have a vibrant team culture where we learn, accomplish and have fun as a team.

Responsibilities:

As a Senior CV Engineer, you will take ownership of designing, prototyping, and productionizing computer vision models for core business scenarios (shelf analysis, product recognition, and synthetic data generation).

- Train and fine-tune CV models with complex data sets, ensuring the delivery of high-accuracy, production-ready results.

- Lead the optimization of the CV inference pipeline for latency, throughput, and cloud resource utilization.

- Architect and develop new CV features in collaboration with cross-functional teams based on evolving customer requirements.

- Define data curation strategies and work closely with the in-house data labeling team to ensure high-quality training datasets.

- Integrate ML models robustly into the end-to-end product flow, supporting real-time and batch inference via cloud-hosted endpoints.

- Establish and maintain MLOps best practices, building automated continuous training pipelines, model versioning, and drift detection.

- Drive innovation through proactive experimentation, prototyping novel model architectures and state-of-the-art training strategies.

- Mentor and provide technical guidance to junior engineers on ML-related features and best practices.

Requirements:

- 2-4 years of professional experience in computer vision or applied machine learning.

- Demonstrated experience working on CV-AI tasks and using/training CV-AI models.

- Deep expertise in ML frameworks such as PyTorch or TensorFlow.

- Proven track record of deploying computer vision models into production environments.

- Strong programming skills in Python and familiarity with ML-related libraries and tools.

- Excellent logical thinking, analytical skills and attention to detail.

- Ability to write structured and production quality code.

- Ability to quickly debug and resolve issues.

- Open to working in a fast paced environment.

- Experience working on cloud environment.

- Bachelor's or Master's degree in Computer Science, Electrical Engineering, Machine Learning, or a related quantitative field.

- Able to join within 30 days of accepting our offer.

Nice to Have:

- Experience with object detection, image segmentation, and classification tasks.

- Familiarity with cloud ML platforms (Azure ML, GCP AI Platform).

- Knowledge of containerization (Docker) and orchestration (Kubernetes).

- Understanding of MLOps principles and tools (MLflow, Kubeflow).

- Experience with synthetic data generation techniques and tools.

- Prior work in CPG analytics or retail technology.

Why apply to this company:

- High Impact: You will be a foundational member of the team, heavily influencing our technology choices and product direction.

- Cutting-Edge Roadmap: Opportunities to work on integrating advanced Computer Vision and AI directly into our retail analytics products.

- Culture: A culture of transparency, collaboration, and mutual respect.