Job Description 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 Experience : 2 - 7 Yrs Job Location : Bangalore/Delhi/Mumbai (ref:hirist.tech),
Employement Category:
Employement Type: Full time Industry: IT Services & Consulting Role Category: Not Specified Functional Area: Not Specified Role/Responsibilies: Data Science Engineer - Machine Learning Job