We are seeking a hands-on Senior MTS, AI/ML Research Engineer, with 6–10 years of experience in researching, designing, building, deploying and optimizing scalable AI/ML solutions for real-world, production-grade applications.
About the role
The ideal candidate should demonstrate strong technical ownership, deep coding capability and a proven record of practical AI implementations, supported by projects, GitHub contributions or production deployments.
Key responsibilities
- +Design, develop, deploy and technically own scalable AI/ML models and solutions for real-world business problems
- +Lead the implementation of AI-driven solutions from technical design through production readiness
- +Drive model optimization for performance, scalability, reliability and production deployment
- +Collaborate with engineering, product and operations teams to translate complex business requirements into robust AI solutions
- +Provide technical guidance through code reviews, solution discussions and reusable engineering practices
- +Evaluate and adopt relevant advancements in AI, machine learning and generative AI for practical business applications
- +Contribute to and maintain high-quality code repositories, development standards and reusable components
- +Drive or contribute to edge AI and real-time AI applications where relevant
- +Demonstrate active participation in coding communities and maintain a strong practical portfolio through GitHub, Kaggle, open-source work or comparable implementations
Required skills and qualifications
- +6–10 years of hands-on experience in AI/ML development, with strong AI coding expertise using Python
- +Strong practical experience with AI/ML frameworks such as TensorFlow, PyTorch and scikit-learn
- +Strong familiarity with APIs, microservices and cloud platforms such as AWS, Azure or GCP
- +Exceptional problem-solving and critical-thinking skills, with the ability to independently handle complex technical challenges
- +Demonstrated ability to take AI solutions toward scalable, production-ready implementations
- +Strong practical knowledge and demonstrable implementation experience over purely academic credentials
Preferred qualifications
- +Strong background in IoT/embedded systems
- +Experience working in manufacturing or industrial domains
- +Contributions to open-source projects or a strong, active GitHub portfolio
- +Experience with MLOps, CI/CD pipelines, model monitoring and production AI/ML operations
- +Experience mentoring engineers or providing technical direction on AI/ML projects