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Job Description
We are seeking candidates with 4–6 years of hands-on experience in Computer Vision, with strong expertise in relevant computer vision technologies and applications.
What your average day would look like:
Collaborate with product and engineering teams to understand requirements and devise possible solutions.
Explore existing research papers, ideas and codebases that can be leveraged in current tasks.
Search for open source datasets and/or design synthetic data pipelines (including data augmentation).
Devise and implement experiments using DL/ML models.
Evaluate the experiments to find failure patterns and come up with improvements in data/model architecture/loss function etc.
Communicate results and ideas to key stakeholders.
Optimize the models for production and collaborate with software engineers for deployment. Must have skills:
Hands-on experience in dealing with image data and CNN based architectures
Should have worked on deep learning frameworks (like pytorch, tensorflow, keras etc.)
Proficient in Python and packages like Numpy, Pandas, OpenCV
Good understanding of data structures and algorithms along with OOPS, Git, SDLC
Mathematical intuition of ML and DL algorithms
Good understanding of Statistics, Linear Algebra and Calculus
Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical analyses
Highly desired:
Hands on experience with latest computer vision model architectures and concepts like ViTs, GANs, Diffusion, Vision Language Models
Knowledge of training and inference optimizations using CUDA, C++, ONNX, TensorRT, OpenVino etc. and profiling of ML pipelines
Worked on building production level APIs for serving models (Flask, Django, TF Serving)
Hands-on experience of using MLOps tools.
Champion best practices in data science, model development, and deployment while promoting a culture of continuous learning within the team.
More Info
Key Skills
GANs
OpenVino
TF Serving
CNN based architectures
TensorRT
ONNX
Vision Language Models
Model Evaluation
ViTs





