Posted:2 days ago|
Platform:
On-site
Part Time
Role - Algorithm Engineer
Experience - 8-13 Years
Salary - UpTo - 60 LPA
Location - India - Chennai
We are looking for an experienced Algorithm Engineer to drive the development, optimization, and deployment of advanced deep-learning and computer-vision models. The ideal candidate will have strong expertise in model architecture design, training workflows, data preparation, and performance evaluation. This role requires a deep technical understanding of AI/ML concepts, the ability to translate complex ideas clearly, and leadership in technical discussions and experimentation.
The Algorithm Engineer will be responsible for designing, developing, and implementing algorithms to solve complex problems. The ideal candidate will have a strong background in mathematics, computer science, and data structures. The Algorithm Engineer will work closely with other engineers and researchers to develop and optimize algorithms for various applications.
Design, tune, and evaluate state-of-the-art deep-learning architectures such as U-Nets, YOLO variants, or similar models.
Explore and implement new modelling approaches and run comparative experiments for new technical challenges.
Lead data purification efforts including dataset filtering, augmentation, optimization, and applying transfer learning strategies.
Define success metrics and perform detailed analysis of model performance across tasks and datasets.
Present findings effectively through visualizations, technical reports, and internal presentations.
Collaborate with engineering teams to develop deployment strategies and choose the most suitable algorithmic solutions for real-world constraints (latency, hardware limits, accuracy requirements).
PhD with 5+ years of experience OR MS/MTech with 8+ years in algorithm development.
Strong background in deep learning and computer vision.
Hands-on experience with PyTorch, end-to-end model-training pipelines, and experimentation workflows.
Strong ability to communicate complex technical concepts and lead algorithm-focused discussions.
Experience with experiment-tracking tools such as TensorBoard, Weights & Biases (W&B), or similar.
Familiarity with cross-platform development, system integration, and deployment environments.
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