Applied Computer Vision Engineer

Job Summary

As an Applied Computer Vision Engineer, you will be working on the state-of-the art challenges in Computer Vision solving them with novel algorithms and optimizations. The majority of our work is focused on applied Computer Vision - so a good understanding of the current state of the art of models (Classification, Object detection, Object Recognition, OCR, LayoutML, GAN etc networks) is mandatory. Were looking for someone who loves to solve problems and enjoys building algorithms and models that identify all possible scenarios. You must enjoy breaking down a problem statement into smaller chunks and have a knack of designing scalable systems using modular pieces.

A day in your role will involve any of the following (or a combination):

• Understanding business objectives and developing Computer Vision based solutions that help achieve it.
• The software could involve training framework, inference framework, working with different technologies for ML.
• Understand the requirements in depth and give adequate time estimates for the features
• Develop processes for different common operations of the team: data acquisition, model training, prototype development.
• Finding open-source datasets for prototype development.
• Develop pipelines for data processing, augmentation, training, inference and active retraining.
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Deploying models to production
• Optimize models for performance at the edge
• Coordinate with QA for every feature and make sure releases are bug free

This is a full time position based out of Noida.

Qualifications

• Bachelors/Masters degree in Computer Science/Computer Engineering/IT or related fields
• 1-2 years of experience. Exceptional candidates with less experience are welcome to apply
• Sound knowledge of various deep learning classification models and object detection models
• Experience of working with Image Video Processing (OpenCV, Scikit, GStreamer, Tensorflow, PyTorch, NVIDIA Deepstream, TensorRT, Keras, Model Training/Inference, Video Processing Pipelines, Different GStreamer Convertors etc)
• Good knowledge of statistics relevant to Deep Learning and ability to use the right statistical measures to assess models performance
• Strong experience with Python and writing reusable code
• Experience with Python web framework, e.g. Flask, Django or FastAPI
• Experience with databases (MongoDB, Postgres, etc)
• Experience with cloud environments for software development and deployment (AWS, Azure, GCP)
• Experience with utilizing various GPU-based training infrastructures
• Experience with Docker
• Knowledge of DevOps and MLOps best practices for production Machine Learning systems
• Experience in optimizing and pruning models, converting models to NVIDIA TensorRT etc would be preferable
• Experience with Azure, Azure ML Studio framework etc. will be preferred
• Prior experience in taking at least one solution to production from Concept to Deployment
• Fluent in using the tools of the trade: Testing, Editors, Git, Command line, Slack

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.