As a senior mechanical engineer at Swaayatt Robots, you are expected to manage, conceptualize and develop innovative products, hardware, electromechanical actuation systems, vehicles, and robotic systems. Key responsibility is to ensure commercial-grade finishing of the manufactured or fabricated mechanical parts or systems, taking the dimensional or geometrical constraints into account, when designing such parts for after-market vehicles, or when integrating with the OEMs. Any system mounted externally or additionally on a commercial vehicle should be aesthetically appealing as well, and as a senior mechanical engineer, this is going be your responsibility to ensure the simulated designs are manufactured or fabricated with very high precision.

Motion planning engineer at Swaayatt Robots will primarily be responsible for implementing existing state-of-the-art or proprietary algorithms for various applications, including for autonomous driving. Secondarily, motion planning engineer will also be responsible for developing novel motion planning algorithms and navigational algorithmic frameworks, including developing decision making algorithmic pipelines, for autonomous vehicles. Typically such an engineer is expected to have the knowledge of the motion planning literature from 1995 till date, having worked on majority of, or have practical experience working deeply in at least two/three of, the motion planning paradigms listed below:

Along with that, knowledge of path tracking algorithms or controllers, and mathematical knowledge of the dynamics and kinematics of standard robotic/vehicle models is also required.

A  Motion planning Research scientist (RS) at Swaayatt Robots will be responsible for conceptualizing and developing motion planning and decision making algorithmic frameworks for various complex and stochastic traffic scenarios, to achieve level-5 autonomy. Motion planning RS should be comfortable working on projects involving multidisciplinary theoretical concepts, foremost of which are traditional motion planning, reinforcement learning (RL) and stochastic processes, topology theory, and manifold theory.

RL Research Scientist (RS) at Swaayatt Robots will be responsible for conceptualizing, theorizing and developing novel decision making algorithmic frameworks to enable autonomous vehicles to negotiate complex, stochastic and adversarial traffic situations. RS is expected to work at the intersection of theoretical computer science (ML, RL, game theory, graph theory, heuristic search, mathematical optimization), motion planning, and pure and applied mathematics.

RL Research Scientist is also expected to optimize and scale the existing proprietary algorithmic frameworks at Swaayatt Robots, such as the Off-Shift Policy framework, Two-Lanes Overtaking Policy framework, and the Multi-Agent Intent Analysis and Negotiation framework. These algorithmic frameworks typically require working at the intersection of following areas: RL, Inverse-RL, ML, Heuristic Search, Topology Theory, Mathematical Optimization, Graph Theory, Manifold Alignment.

Machine learning research scientist at Swaayatt Robots is responsible for articulating, designing and developing custom ML/DL/RL algorithms for various robotic and autonomous driving applications, along with doing foundational research in developing novel algorithmic frameworks for autonomous vehicles negotiating complex traffic scenarios. ML research scientist is required to have the mathematical aptitude and the ability to work on projects involving multidisciplinary theoretical concepts and ideas.