Applied Computer Vision Engineer (1+ Years) - Onsite -Noida

Role overview
First and foremost, we're looking for people who are excited about what we're doing. We're building in a relatively new space, so you'll be able to use your creativity to help us solve problems and delight our customers.
As an Applied Computer Vision Engineer, you will be working on the state-of-the art challenges in the field of Computer Vision & solving them with novel algorithms and optimizations. 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.
We’re 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 list is not exhaustive at all, and you'll have a lot of autonomy over your work.
This is a full time position based out of Noida. During the interview, you'll be able to share what you're most interested in.

About you

• None of these are requirements, but do describe the kinds of people that we think would be most effective at Syook right now.
• Love thinking broadly about problems and thinking creatively about how to solve them efficiently.
• Happy to try things out to validate new features, and move on if they no longer solve a problem.
• Excited for a front-row seat into a fast growing, early stage company. Things will change a lot!
• Enjoy thinking through trade-offs, with both mindfulness of short-term needs and our long-term direction.
• Happy writing documentation so that others can ramp up super easily and you're never a single-source-of-failure. We're a bit too small to have silos.
• You are driven and care about doing a good job and improving your craft.
• You have a growth mindset, can keep up with the latest technology changes and trends and suggest enhancements based on these
• Most importantly, you’re the kind of person who is friendly, approachable, ready to help others and personally driven to put your best foot forward.

Technically these are some of the things we would like for you to have to be able to contribute effectively in this kind of a position:

• Bachelors/Masters degree in Computer Science/Computer Engineering/IT or related fields
• 1+ 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 model’s 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