- Lead the development and deployment of end-to-end machine learning solutions for biometric applications including face, speaker, fingerprint, palmprint, and eye socket-based identification.

- Drive the design of scalable and robust ML systems, ensuring modularity and portability across mobile (Android/iOS) and web environments.

- Conduct and oversee ML experimentation, model evaluation, and A/B testing to determine model efficacy in real-world scenarios.

- Implement rigorous model validation frameworks to ensure reliability, fairness, and generalization of models.

- Collaborate with cross-functional teams to integrate models via RESTful APIs using FastAPI, ensuring smooth interaction with mobile, web, and backend systems.

- Benchmark and optimize edge performance on deployment targets such as TFLite (Android), CoreML (iOS), and WebAssembly (browser).

- Maintain clear documentation of system designs, experiment results, benchmarks, and APIs.

- Provide technical mentorship and participate in design/code reviews to uphold engineering best practices.

Requirements and Skills :

- Solid experience designing and developing ML systems at scale, including data preprocessing, training, evaluation, and deployment.

- Deep understanding of system design principles tailored to ML architectures.

- Practical expertise in model experimentation, hyperparameter tuning, and validation pipelines.

- Experience conducting A/B tests and using the results to drive model and system improvements.

- Strong knowledge of API integration techniques, particularly with FastAPI, for interfacing ML models with production systems.

- Exposure to edge benchmarking tools and optimization strategies for mobile/web deployments.

- Proficiency in Python, with experience using ML libraries such as PyTorch or TensorFlow, Scikit-learn, etc.

- Excellent problem-solving, analytical, and communication skills.

- Ability to thrive in a fast-paced R&D setting with minimal supervision.

- Prior experience in the biometric domain is a strong advantage.