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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand plus mid-level Bangalore role but specialized edge-AI skills reduce broad applicant competition.
Edge ML, CUDA, Triton, and on-device deployment expertise limits transferability across industries.
Explicit 4-7 years, specialized ML/CUDA/PyTorch and deployment skills create stringent screening filters.
Job Description
Structured overview of role & requirementsAbout This Role
Develop, train, validate, and deploy machine learning models specifically for production edge AI environments, ensuring scalability and reliability.
Design, optimize, and maintain ML pipelines and systems including hyperparameter tuning to maximize model performance and efficient integration with CI/CD processes.
Lead ML system design and experiments, collaborate with cross-functional teams to enhance automated model training and apply ML/statistical modeling to solve business or research problems.
Minimum Requirements
Bachelor's or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or related field, or equivalent experience.
4-7 years of relevant work experience in machine learning, programming, algorithms, or related field; or advanced degree with 3-5 years experience.
Proficiency in programming languages and tools including C++, Python, CUDA, PyTorch, Scikit-learn, and knowledge of ML algorithms, deep learning, NLP.
Work location: India; Full-time role with no relocation or travel requirements.
Ideal Candidate Profile
Experienced in developing and deploying machine learning models in edge AI or production environments with focus on scalability and system reliability.
Strong background in software engineering practices integrated with ML, including CI/CD collaboration and pipeline development.
Capable of leading projects or teams by providing direction on ML experiments and model training, impacting multiple teams and decision-making processes.