Robotics Engineer

About CynLr

As a foundational technology building company in Robotics & AI, CynLr builds visual robots that can intuitively learn to pick & handle even unknown objects without requiring any prior training, just like a human baby fiddling with objects. CynLr calls this stack Object Intelligence (OI).

From fitting a screw to removing object out of its the plastic wrapper to automating the assembly of a car/gadget - every such object handling task that involves "adapting on the fly" is not prior trainable & thereby remains non-automatable across the industries

.
With OI's ability to learn on the fly, CynLr’s focus is to universally automate factories and eliminate the need for complicated custom machines to manufacture product

s.
Thereby simplifying manufacturing into Universal Factories, which can be programmatically repurposed to produce a wide variety of Products. CynLr envisions the future factories to be decentralized, micro factories (not the Giga Factories) that could rather be hosted in your street-ends; opening up the possibility of Personalized Products – liberating design of products from the constraints of manufacturabili

ty.
As a Robotics Engineer, you will develop physics-based simulations, optimize multi-arm robotic workflows, and integrate AI-driven control systems. This role involves designing, validating, and optimizing robotic motion, perception, and manipulation algorithms for real-world applications. You'll collaborate across hardware, software, and ML teams to enhance robotic autonomy and effici

ency
Physics-Based Simulation Develo

• pmentDevelop comprehensive physics-based models of robotic systems, environments, and interact
• ions.Create and validate dynamic models incorporating rigid body dynamics, contact physics, and material properties, and compliance for multi-arm robotic sys
• tems.Build digital twins of physical robots and environments to replicate real-world scena

rios.
Algorithm Development & Implemen

• tationDesign, implement, and validate control and motion planning algorithms for multi-arm robots, focusing on customer manipulation and grasping
• tasks.Optimize and integrate kinematics, dynamics, and force-based control strategies for real-time applica
• tions.Support implementation of learning-based algorithms for real-time perception and manipulation tasks, including simulation-based testing and valid

ation.
Machine L

• earningLeverage ML for robotic applications (e.g., perception, decision-m
• aking).Implement learning-based algorithms for real-time perception and manipulation

tasks.
Testing, Validation & Optim

• ization:Establish simulation validation protocols to bridge virtual and real-world performance, ensuring accuracy and reli
• ability.Develop automated test sequences and metrics to validate algorithms across diverse scenarios with varying parameters (e.g., lighting, sensor noise, object positions, contact pro
• perties)Analyse simulation results to optimize robotic systems for performance, safety, and reliability, proposing design improvements (architecture, algorithms, or techno

logies).
Collaboration & Cross-Functiona

• l SupportCollaborate with control engineers to validate and tune control systems in si
• mulation.Collaborate with Algo and software/hardware teams to refine algorithms, identify and address sequencing errors, corner cases, and bot
• tlenecks.Provide actionable insights from simulation analyses to guide system impr

ovements.
Documentation &

• ReportingDocument simulation methodologies, assumptions, and validatio
• n results.Provide detailed reports on system performance, optimization opportunities, and experimenta

l findings
Must have an Under

• standing ofAdvanced physics-based modelling and numeric
• al methods.Robot kinematics, dynamics, and control syst
• ems theory.Simulation validation and verification
• techniques.Sensor modelling (cameras, force/tor
• que, etc.).Experience with motion planning

algorithms.Engineering &

• ; Analysis:System dynamics modeling and erro
• r analysis.Test plan development and root caus
• e analysis.Solution feasibility studies and model validation met

hodologies.
Good to Have

• Experiences:Machine learning frameworks (e.g., PyTorch, TensorFlow), Computer Vision, and real-time control system imp
• lementation.NVIDIA Isaac Sim/Omniverse, CoppeliaSim, Mujoco, PyBullet, PhysX, Gazebo, or similar physics-based simulation
• frameworks.Python and C++ for motion scripting and
• automation.CAD software integration and version control sy