Assistant Manager | AI Engineer | Bengaluru | Sustainability & Emerging Assurance
Deloitte (company site, opens in a new tab)3–6 yrsBengaluruOn-siteDirect career pageEst. 15–30 LPA
Posted on 28 Sept
Reach people at Deloitte
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Deloitte you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and deploy AI-powered autonomous systems integrating robotics, sensors, and edge computing for real-world physical environments.
- Collaborate across robotics, software, hardware, and product teams to build scalable AI models and autonomous decision-making algorithms including navigation and motion control.
- Optimize AI models for real-time edge deployment, validate solutions using simulation/digital twins, and improve system performance, reliability, and operational efficiency.
Minimum Requirements
- Bachelor's or Master's degree in Computer Science, AI, Robotics, Electronics, Mechatronics, or related discipline.
- 3–6 years of professional experience in AI, machine learning, robotics, or autonomous systems.
- Proficient programming skills in Python and at least one of C++ or Java; experience with ML/DL frameworks such as PyTorch, TensorFlow, or Keras.
- Hands-on experience with computer vision, sensor integration, robotics frameworks like ROS/ROS2 and Gazebo, autonomous navigation, and edge device deployment.
Ideal Candidate Profile
- Strong domain expertise in AI for robotics, including sensor fusion, autonomous navigation, and real-time edge optimization.
- Experienced working in multidisciplinary engineering teams covering robotics, software, and hardware integration.
- Familiarity with advanced AI techniques such as reinforcement learning, generative AI for robotics, GPU acceleration, and cloud-based MLOps and CI/CD for model lifecycle management.