We are seeking a motivated and enthusiastic C#.NET Developer (Fresher to 3 years' experience) to join our growing development team. The ideal candidate should have a solid understanding of the .NET Framework, along with academic or project-based exposure to WPF , WCF , or WinForms . This is an excellent opportunity for a recent graduate or entry-level developer to gain hands-on experience in designing, developing, testing, and maintaining desktop applications in a collaborative and fast-paced environment. Responsibilities: Develop and maintain applications using C#.NET , WPF , WCF , and WinForms Design, build, and support scalable and reusable components Collaborate with cross-functional teams to define, design, and ship new features Maintain code quality through unit testing and code reviews Optimize applications for performance and scalability Write clean, efficient, and well-documented code Troubleshoot and resolve bugs and performance issues Participate in Agile/Scrum meetings and contribute to planning and estimations Requirements: Strong foundational knowledge of software development using C#.NET , with hands-on experience through academic projects or internships. Strong working knowledge of: WPF (MVVM pattern) WinForms WCF (SOAP/REST services) Solid understanding of object-oriented programming and design patterns Experience with version control systems (e.g., Git, TFS) Familiarity with database technologies (e.g., SQL Server, SQLite, Entity Framework) Ability to debug and optimize existing code Strong problem-solving and analytical skills Good communication skills and ability to work both independently and in a team Preferred Skills (Optional but a Plus): Experience with .NET Core/.NET 5/6 Familiarity with third-party libraries like Telerik or DevExpress Exposure to CI/CD pipelines and DevOps practices Knowledge of Agile/Scrum methodologies Education: Bachelor's degree in computer science, Engineering, or related field Compensation: Competitive salary based on experience Professional development opportunities

The Electronics Lead will be responsible for the full lifecycle design, development, and integration of advanced electronic and embedded systems. The individual must possess expert-level knowledge across circuit design, PCB development, hardware-software interfaces, and power electronics. In addition to hands-on engineering leadership, the candidate will manage a cross-functional team of up to 10 engineers, overseeing system architecture, technical delivery, and timeline adherence. This role combines deep technical execution with project and team leadership responsibilities. Core Technical Responsibilities- Circuit Design & Architecture Analog and digital circuit design including low-noise analog front ends and high-speed digital systems Signal integrity control, differential pair routing, impedance matching, cross-talk mitigation Power domain isolation, reverse polarity protection, over-voltage and thermal protection circuit design DC-DC converter design (buck, boost, SEPIC, flyback, synchronous) Integration of op-amps, comparators, analog switches, voltage references Multi-Layer PCB Engineering Design of multi-layer PCBs (up to 16 layers) with controlled impedance and RF optimization Layout of DDR3/DDR4, PCIe, USB 3.0, LVDS, and MIPI high-speed interfaces Compliance with IPC-2221, IPC-7351, MIL-STD for rugged embedded systems Experience in Altium Designer, OrCAD/Allegro, PADS, and KiCAD Embedded and Peripheral Interfaces Serial and digital interfaces: UART, USART, SPI, I2C, TWI, RS-232/485, USB-OTG UAV and control protocols: PWM, PPM, SBUS, IBUS, CAN 2.0A/B, CAN-FD, UAVCAN Ethernet interfaces (RMII, RGMII), USB-C PD, GPIO-based control logic with interrupt servicing Flash memory interfaces: QSPI, SDIO, eMMC, NAND/NOR Microcontroller and SoC Expertise STM32F0/F1/F3/F4/F7, L0/L4/L5, H7/H5 architectures with HAL/LL-level firmware development Bare-metal and RTOS (FreeRTOS, ChibiOS) design DMA optimization, timer/PWM channels, ADC/DAC interfacing Bootloader development (UART/I2C/USB/DFU), in-field firmware upgrade architecture Debug via JTAG/SWD, trace analyzers, runtime profiling Advanced Processor and Accelerator Systems NXP i.MX6/i.MX8, TI AM437x/AM62x, Zynq 7000/Zynq Ultrascale+ PCIe Gen 3/4 routing and endpoint design High-speed memory interfaces (LPDDR4, DDR4, eMMC, UFS) Accelerator cards (Jetson Orin, Coral Edge TPU, Movidius, FPGA PCIe) Power Electronics and Energy Systems BMS and BTMS architectures for Li-ion, Li-FePO4 cells with passive/active balancing Load management with MOSFET/IGBT-based switching, precharge circuits SMPS topologies, HV isolation, GaN/SiC integration for high efficiency Battery protection, coulomb counters, NTC/PTC thermistor integration AC-DC conversion with flyback, PFC correction, and fail-safe logic Sensor and IO System Integration MEMS sensors: IMU (gyroscope, accelerometer, magnetometer) integration GNSS modules (NMEA, UBX, RTK correction) Resolver, encoder, and Hall-based motion feedback systems Opto-isolators (PC817, TLP250, 6N137), digital isolators (ISO7731, Si86xx) Surge protection using TVS, MOV, and filter networks System-Level Integration and Safety ISO 26262-compliant functional safety architecture Hardware watchdogs, overcurrent and brownout protection, redundancy control paths MIL-STD-461G, DO-160 EMI/EMC planning and testing methodology Fault-tolerant design strategies with primary-secondary system logic Support for mission-critical logging and Health Monitoring (HUMS) Testing and Validation Tools Oscilloscopes, logic analyzers, spectrum analyzers, and protocol decoders STCubeMonitor, CANalyzer, Saleae, UART/I2C/SPI bus sniffers Simulation with LTspice, PSpice, MATLAB/Simulink Signal/power integrity analysis using Ansys SIwave, HyperLynx Project & Team Leadership Responsibilities Lead a multidisciplinary team of up to 10 electronics and embedded engineers Define technical architecture, design reviews, and verification strategies Plan and execute project phases: requirement capture, design, prototyping, and validation Ensure quality control, EMI/EMC compliance, and performance benchmarking Coordinate cross-functional deliverables across hardware, firmware, and testing Track project milestones, resource allocation, and technical documentation Mentor junior engineers in best practices, debugging, and advanced R&D techniques Preferred Qualifications M.Tech / Ph.D. in Embedded Systems, Electronics, Avionics, or Microelectronics 10+ years of experience in electronics system design and team leadership Exposure to aerospace, defense electronics, automotive ECUs, or UGV systems Proven record in complex embedded product delivery, patents, or technical publications

Job Description We are hiring an expert-level Embedded Firmware Engineer with 5+ years of hands-on experience in real-time C++ development for high-throughput robotics platforms. The role involves architecting low-latency control systems, mathematically rigorous estimators, and secure firmware logic on deterministic embedded targets using modern C++ (C++17/20/23) . This is a critical role for embedded autonomy development, demanding mastery of software architecture , numerical precision , and security robustness . Core Technical Responsibilities- Advanced C++ Systems Programming (C++17/20/23) Deep understanding of template metaprogramming (variadic, fold expressions, constexpr evaluation) Use of CRTP, policy-based design, static interface dispatch Custom STL-compliant containers, allocators, and compile-time dataflow Scoped RAII, intrusive data structures, deterministic memory systems (no heap) Advanced use of std::tuple, std::variant, std::optional, std::bitset, std::span, and metaprogramming utilities Static polymorphism, tag dispatching, traits-based compile-time configuration Real-Time Scheduling and System Architecture Design of cyclic executive frameworks and rate-synchronized control threads Event, signal, and time-triggered architecture (TTA) models Hard real-time response logic (bounded jitter and latency), DWT-based profiling Lock-free ring buffers, MPSC queues, memory barriers, and interrupt-safe containers RTOS integration with custom schedulers, zero-overhead task dispatch logic Support for layered deterministic execution: low-rate navigation, mid-rate estimation, high-rate control Robotics Math & Control Systems Rigid body kinematics: transformation trees, link frames, inertia matrices Control loop design: PID, cascaded PID, LQR, state-space controllers Quaternion and rotation vector math with Eigen or equivalent math engines Kalman filters (EKF, UKF), complementary filters, IMU fusion Matrix decompositions (LU, QR, SVD), Jacobian computation, motion models Analytical vs numerical differentiation for robot joints, manipulators, or flight platforms Covariance propagation, Mahalanobis distance checks, anomaly detection filters Cryptography and Secure Embedded Design Cryptographic primitives: AES-GCM/CTR, ChaCha20, Poly1305, ECC, RSA Secure boot, image signing, key attestation, and anti-rollback HMAC-SHA256, CMAC-AES, and protocol-safe hash chains Key storage, tamper-resistance, nonce usage, and memory scrubbing Constant-time implementations, protection against timing, DPA/SPA side-channels Lightweight TLS-style handshake for telemetry encryption or OTA control Architecture, Tooling, and Testing Layered firmware architecture with clean separation: drivers, logic, math, crypto, and interface Static scheduling frameworks vs dynamic priority queues (hybrid RT models) Unit testing using GoogleTest or Catch2; mocking of deterministic hardware states Static and semantic analysis: Clang-Tidy, MISRA, Coverity, Sanitizers Host simulation of logic models using abstraction layers and input mocking Cross-platform toolchains (ARM GCC, Clang), CMake advanced usage, GitLab CI/CD pipelines Preferred Qualifications B.Tech / M.Tech / Ph.D. in Embedded Systems, Robotics, Control Engineering, or Computer Science 5+ years of experience in real-time embedded firmware on robotics or autonomous systems Strong applied mathematics and control systems engineering background Track record of contributions to robotics, motion control, or autonomous navigation firmware stacks Experience with Eigen, MicroEigen, TinyEKF, mbedTLS, or custom C++ math engines Exposure to secure robotic firmware design, SLAM systems, or high-frequency control kernels

We are looking for an experienced High-Performance Computing (HPC) Engineer to design, develop, and optimize computational systems and software for large-scale data processing, simulations, and advanced analytics. The ideal candidate will have strong programming skills in C/C++ and experience with parallel computing, performance tuning, and HPC infrastructure. Key Responsibilities: Develop and maintain high-performance software using C/C++, focusing on parallel and distributed systems. Optimize code for multi-core CPUs and GPU architectures using OpenMP, MPI, CUDA, or OpenCL. Profile, benchmark, and debug performance-critical code using tools like gprof, Valgrind, VTune, or nvprof. Collaborate with researchers and developers to adapt scientific algorithms for scalable computing. Work with Linux-based systems to manage HPC environments and integrate job schedulers such as SLURM or PBS. Contribute to the design and scaling of HPC systems and clusters. Support users in porting, debugging, and optimizing applications on HPC platforms. Required Skills: Proficiency in C/C++ with strong fundamentals in memory management and performance optimization. Hands-on experience with parallel computing frameworks: OpenMP, MPI, CUDA, or OpenCL. Knowledge of system-level programming and Linux development environments. Familiarity with profiling and debugging tools for both CPU and GPU. Understanding of computer architecture, concurrency, cache optimization, and SIMD/vectorization. Experience with version control systems such as Git. Preferred Qualifications: Familiarity with scientific computing libraries (e.g., Eigen, LAPACK, cuBLAS, PETSc, Trilinos). Experience working with HPC clusters, file systems (Lustre, GPFS), and InfiniBand or high speed interconnects. Exposure to real-time or robotics simulation environments. Knowledge of numerical analysis and floating-point computation issues. Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Physics, or a related technical field.

Advanced Terrain-Aware Perception Implement material-specific semantic layers (soil, sand, gravel, bed-rock, tall grass, shallow water, snow, ice) that update every frame and age-out when confidence degrades. Derive surface normal, roughness, cohesion and expected sink-age from texture statistics + monocular depth cues. Compute instantaneous grade (), side-slope, slip angle and flag combinations that exceed rollover or traction thresholds. Detects ruts, berms, holes and negative obstacles by fusing long-baseline disparity with shading gradients and shadow parallax. Class-specific hazard masks (e.g. sage-brush vs. tumbleweed vs. basalt outcrop) that feed directly into the traversability cost map. WheelTerrain Interaction Estimation Fuse visual shear-flow with wheel tachometry to produce online slip-ratio and effective (friction coefficient) per wheel. Predict sink-in depth (sand / snow) from colour histogram shifts and wheel torque spikes. Raise soft faults when wheelground contact probability less than0.3 (airborne cresting, pothole drop-in, obstacle hang-up). Real-Time Route Feasibility & Micro-Planner Hooks Transform pixel-level terrain classes into steer-able corridors and hazard polygons with less than 25 ms latency. Prioritise dynamic re-weighting of cost metrics (e.g. favour firmer gravel over muddy shortcut when rainfall detected). Extreme Environment Hardening Design visibility-fallback perception: Short-range active illuminator gating for dust / snow glare. Polarised camera processing for water-surface discrimination. Thermal fusion when visible light SNR less than 6 dB. Implement turbulence-robust line detection to keep horizon and vanishing-point estimates stable during heat shimmer. Self-Consistency Audits Every 100 ms run terrain confusion matrixdrop or re-sample tiles whose posterior variance greater than 2_thresh. Maintain loop-closure integrity score for vision odometry; trigger re-initialisation if drift greater than 2 % of path length within 30 s. Additional Required Expertise Area Advanced Expectation Photometric Stereo Reconstruct micro-surface undulations for traction estimation without LIDAR. Rolling/Center-of-Mas s Stability Predict rollover using tilt-vector + speed + suspension travel in real time. Dust & Snow Morphology Implement particle-size adaptive temporal filtering to separate airborne particulates from solid obstacles. Realtime SIMD / DSP Hand-vectorise convolutional kernels for ARM NEON or x86 AVX-512 where no GPU is present. Failure Injection Design unit tests that inject random camera blackout, saturated highlights, frame drops, inertial spikesand verify graceful degradation. Bonus Capabilities Built perception for Dakar-class rally bots, planetary rovers or Online Desert Challenge vehicles. Published work on vision-based slip prediction or terrain type transfer learning in CVPR, ICRA or RA-LAT. Experience creating synthetic terrain datasets with physically-based rendering for rare surfaces (lava crust, talc powder dunes). Knowledge of acoustic ground contact sensing and correlating it with visual classification for redundancy.

We are seeking a Senior Robotics Engineer with extensive expertise in developing end-to-end robotic autonomy systems . The candidate must demonstrate deep capability in real-time control , multibody dynamics , optimal motion planning , and state estimation . The role demands rigorous system-level thinking, cross-disciplinary coordination with embedded and software teams, and research-grade mathematical modeling skills applied in real-world autonomous platforms. Key Technical Responsibilities- Robot Kinematics and Dynamics Advanced inverse and forward kinematics for serial, parallel, and mobile robots SE(3), SO(3), Lie group operations and coordinate transformation pipelines Analytical Jacobians, manipulability metrics, singularity resolution Inverse dynamics using recursive NewtonEuler and Lagrangian mechanics Floating-base dynamics, contact models, and hybrid system simulation Payload-compensated control, inertial parameter identification, external force rejection Control Systems (Model-Driven and Real-Time) Multi-loop cascade control for position, velocity, and torque domains Linear and nonlinear control system design (PID, LQR, MPC, adaptive control) Full-state feedback controllers with observer integration Trajectory stabilization using feedback linearization or robust Lyapunov techniques Control saturation, switching logic, anti-windup, and stability margin guarantees Real-time controller deployment on embedded or hard-real-time platforms Estimation & Sensor Fusion Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and information filters IMU, GPS, visual odometry, magnetometer, encoder fusion pipelines Drift modeling, bias estimation, and covariance bounding Nonlinear observer design and uncertainty propagation SLAM backend optimization, graph-based estimation pipelines Time synchronization and latency compensation between asynchronous sensors Motion Planning and Autonomy Kinodynamic motion planning with collision checking and constraint enforcement Trajectory optimization (minimum-jerk, time-optimal, energy-optimal) Sampling-based algorithms (RRT, RRT*, PRM) and trajectory smoothing Local reactive planners (DWA, TEB) integrated with global planners Real-time re-planning in dynamic environments Path-following with differential flatness-based control Mathematical & Computational Tools Strong command of Eigen , Ceres Solver, CasADi, Pinocchio or Drake Matrix decompositions (QR, SVD, Cholesky), convex optimization, constrained solvers Jacobian/Hessian calculation (symbolic or autodiff) for control and planning MATLAB/Simulink, Python/SciPy for prototyping and validation Numerical integration schemes for multibody systems (Runge-Kutta, Lie Integrators) Systems Integration ROS 1/2 deployment pipelines with real-time node scheduling ROS2 middleware customization with DDS tuning for hard real-time Sensor calibration (extrinsic/intrinsic), actuator synchronization Middleware integration with embedded control logic and real-world I/O Latency-aware system architecture for perception-planning-control loop closure Safety-oriented architecture with mode management and failsafe logic Engineering Process & Leadership Lead architecture design across perception, control, and decision layers Perform formal system verification and stability validation Supervise integration of simulation and hardware-in-the-loop (HIL) pipelines Guide junior roboticists in control, planning, and systems modeling Contribute to R&D publications, patents, or technology demonstrators Manage task breakdown, technical risks, and system-level design decisions Preferred Qualifications M.Tech / B.Tech in Robotics, Controls, Applied Mechanics, or Aerospace 4 + years in applied robotics R&D for ground, aerial, or humanoid systems Deep experience in autonomous robot deployments, research publications, or patents Mastery of control theory, estimation pipelines, and robotic software stack (e.g., ROS2, Drake, Pinocchio)

We are seeking a Robotics Engineer with a solid foundation in robotic control systems , kinematics/dynamics , and mathematical modeling , coupled with practical experience in implementing these systems on real-time embedded or high-performance compute platforms. The role involves developing autonomous motion logic , estimation frameworks , and robotic algorithms for field-deployable intelligent machines. Core Technical Responsibilities- Robotics Kinematics & Dynamics Forward and inverse kinematics (serial/parallel manipulators, mobile platforms) DenavitHartenberg (D-H) parameterization, transformation matrices, SE(3) frames Inverse dynamics using Newton-Euler and Lagrangian methods Multi-body dynamics modeling, Jacobian computation, singularity handling Constraint resolution for underactuated or redundant robotic systems Dynamics compensation for payload variation and external disturbances Control Systems Design PID, cascaded PID, feedforward + feedback hybrid control Linear state-space modeling, controllability and observability analysis LQR, pole placement, and optimal trajectory stabilization Model Predictive Control (MPC) basics for path tracking Sensor feedback loop integration (encoder, IMU, force-torque sensors) Saturation, anti-windup, slew rate limiting, and safety interlocks Estimation & Sensor Fusion IMU + magnetometer + GPS fusion using complementary filters or Kalman filters (EKF/UKF) Dead-reckoning, drift compensation, and heading estimation Odometry tracking for differential drive, Ackermann steering, and holonomic bases Sensor latency calibration and outlier rejection filters Covariance propagation and uncertainty bounding SLAM or VIO pipeline understanding (bonus) Math Tools & Simulation Proficient in Eigen for linear algebra (matrices, quaternions, decompositions) Use of MATLAB/Simulink, Python (NumPy/SciPy), or C++ math libraries Simulation using Gazebo, Isaac Sim, Webots, or custom physics engines Motion planning algorithms: A*, RRT, potential fields, trajectory smoothing Testing with synthetic sensor injection and disturbance modeling System Integration Interface with embedded firmware teams for control loop integration Tuning control loops for real-world timing, actuator limits, and environmental response Coordinate frame management (NED, ENU, body-fixed, camera frames) Deployment onto real-time OS or Linux-based compute nodes (ROS 1/2 stack) Real-world calibration procedures: encoder zeroing, IMU alignment, gain tuning Tools & Frameworks ROS 1/2 (navigation, tf, control, message transport) RViz or 3D visualization tools for debugging Git, CMake, and CI pipelines for code validation Logging, playback, and telemetry analysis (e.g., rosbag, custom log viewers) Preferred Qualifications B.Tech / M.Tech / Ph.D. in Robotics, Control Systems, Mechatronics, or Applied Mechanics 3–7+ years of robotics control and estimation experience Strong background in applied mathematics and physical modeling Experience with robotic arms, mobile robots, UAVs, or hybrid autonomous platforms Publications or project contributions in control, planning, or estimation domains

We are looking for an embedded firmware engineer with strong proficiency in modern C++ (C++17/20) and deep understanding of real-time systems , robotic control theory , and embedded cryptography . The ideal candidate will contribute to the development of high-throughput robotic systems , where deterministic execution, safe memory usage, and advanced mathematical modeling are critical. Core Technical Responsibilities- Modern Embedded C++ Development C++17/20 constructs: constexpr, structured bindings, lambdas with capture, fold expressions Template metaprogramming, CRTP, type traits, and SFINAE-based architecture Zero-overhead abstraction using value categories, move semantics, and static polymorphism Strong STL use: std::variant, std::optional, std::array, std::span, and allocators Custom memory pools, ring buffers, and fixed-size containers for allocation-free runtime Compile-time configuration, traits-based component wiring, and feature toggling Real-Time Robotic Control Logic Cyclic and event-driven schedulers with millisecond- and microsecond-precision resolution Tick-accurate rate-grouped control loops (e.g., 100Hz, 400Hz, 1kHz) Cooperative and preemptive task design with determinism and timing guarantees Latency profiling and jitter minimization via DWT counters or hardware timers FSM/HSM state machine design with real-time transitions and priority resolution Implementation of bounded delay, hard real-time response systems Mathematical Modeling for Robotics Vector/matrix math using Eigen or equivalent expression-template math libraries Coordinate transforms: SE(2)/SE(3), quaternion handling, rotation matrices Kalman filters (EKF/UKF), sensor fusion, prediction pipelines Control systems: PID, state-space control, LQR Jacobian-based kinematics, inverse dynamics, torque models Linear algebra: LU, QR decomposition, eigenvalues/eigenvectors Fixed-point math for deterministic runtime modeling on MCUs Embedded Cryptography & Secure Firmware Symmetric crypto: AES-CTR/GCM, ChaCha20-Poly1305 Asymmetric crypto: ECC (Curve25519), RSA-2048 Hashing and message auth: SHA-256, HMAC, CMAC Secure firmware update pipelines, image signing, anti-rollback logic RNG and nonce strategies for handshake protocols Constant-time algorithm design for side-channel resistance Key management and tamper detection logic Software Architecture and Verification Policy-based and layered architecture for hardware-abstraction, logic, and scheduler decoupling Strong separation of concerns and compile-time interface injection Unit tests with mocks/stubs using GoogleTest, Catch2, or Trompeloeil Static analysis with Clang-Tidy, Cppcheck, and sanitizers (ASan, UBSan) Host-based simulation of embedded control logic with reproducible test cycles Build system mastery with CMake (interface targets, generator expressions, cross-compilation) Preferred Qualifications B.Tech / M.Tech in Embedded Systems, Computer Engineering, Robotics, or Applied Mathematics 3+ years of experience in high-performance real-time firmware development Background in real-time robotics, motion planning, or control systems Exposure to secure systems, embedded cryptographic libraries, or robotics middleware Demonstrated ownership of real-time firmware modules in production or research robots

We are seeking a Senior Unity Developer with hardware integration experience , preferably in driving simulator environments , to join our growing simulation team. You will lead the design, development, and optimization of high-fidelity driving simulator systems, ensuring seamless integration between Unity and physical simulator hardware (motion platforms, steering wheels, pedals, sensors, VR headsets). Key Responsibilities: Lead Unity application development for driving simulator systems . Integrate hardware components (motion platforms, steering wheels, sensors) using relevant SDKs and APIs. Optimize application performance for stable, high-FPS simulation environments. Implement realistic vehicle physics and dynamics within Unity. Debug and resolve hardware-software integration issues. Collaborate with hardware and simulation engineers to calibrate and maintain simulator systems. Develop testing and calibration tools for simulator validation. Document integration processes and maintain clean, scalable project structures. Requirements: 3+ years of Unity development experience (C#), with a strong portfolio in simulation or gaming. Proven hardware integration experience (motion platforms, USB HID devices, sensor integration, CAN bus, etc.). Strong understanding of vehicle physics, kinematics, and control systems in simulation. Experience with VR/HMD integration (Quest, Varjo, or similar). Knowledge of rendering pipeline optimization (URP/HDRP) for real-time simulation. Ability to debug and resolve technical issues in complex simulation pipelines. Familiarity with multi-display or projection system integration is a plus. Preferred Qualifications: Prior experience developing driving or flight simulators or any sensor based simulators Experience with motion platform SDKs (SimXperience, DOF Reality, Moog). Knowledge of automotive communication protocols (CAN, LIN) . Experience with ROS or robotics simulation frameworks . Familiarity with AI traffic simulation or scenario generation tools in Unity. What We Offer: Opportunity to work on cutting-edge driving simulator products . A collaborative environment with experienced hardware and simulation engineers. Flexible work arrangements. Growth opportunities within advanced simulation and hardware-software integration . How to Apply: Please submit: Your updated resume/CV . A brief description of your relevant simulator or hardware integration projects . Any GitHub/portfolio links showcasing your work.

🧠 About the Role We are looking for an Autonomous Systems Engineer with strong experience in robotics, controls, estimation, and embedded software. This is a hands-on role where you'll design, implement, and deploy autonomy stacks for UGVs, working across localization, control, sensor fusion, motion planning, and real-time deployment . Your work will be used in the field, integrated into platforms that navigate unstructured environments autonomously. 🔧 What You’ll Work On- 🧭 Localization & Sensor Fusion Implement EKF, UKF, or factor graphs to fuse IMU, wheel odometry, GPS (RTK/L1), magnetometer, and vision-based odometry Real-time dead-reckoning and pose estimation Handle time synchronization, sensor latency, and covariance propagation 🎯 Control Systems Design PID, LQR, and hybrid control architectures for skid-steer / Ackermann platforms Interface via CAN, UART, or shared memory with low-level firmware Trajectory tracking using spline-based and discrete path followers 🛤 Motion Planning Implement planners like A*, D*, RRT*, DWA, and spline-based methods Integrate costmaps, dynamic constraints, and real-time path generation Develop local obstacle avoidance using potential/vector fields 🤖 Robot Modeling Derive forward/inverse kinematics and dynamic models (Newton-Euler, Lagrangian) Handle slip, disturbance modeling, and Jacobian computation Manage SE(3) transforms across body, sensor, map, and ENU/NED frames ⚙️ System Integration (ROS 2) Develop modular autonomy software in ROS 2 using nodes, messages, actions Build architecture for localization, control, planning, and perception Integrate diagnostics, failsafe logic, and heartbeat systems 👁️ Perception (Preferred) Use LiDAR, stereo, depth, or event cameras for terrain analysis and obstacle detection Develop point cloud pipelines (e.g., voxel grid, NDT) and basic semantic segmentation 🧰 Tech Stack & Tools Languages: C++17/20 (multi-threading, hardware abstraction), Python Frameworks: ROS 2 (rclcpp, nav2), CMake, colcon, DDS Libraries: Eigen, Sophus, Ceres Solver, NumPy/SciPy Sim & Debug: RViz, Gazebo, Isaac Sim, rosbag, custom loggers Hardware: Jetson, STM32, RTOS, CAN, SPI, I2C ✅ What You Bring B.Tech / M.Tech / Ph.D. in Robotics, Mechatronics, Controls, or CS/EE with robotics specialization 4+ years of hands-on experience in real-world robot autonomy Strong fundamentals in: Kinematics & Dynamics Estimation & Filtering Feedback & Motion Control C++ and Linux-based robotics development Proven deployment on physical platforms (not just simulations) 🎯 Why Join Us? Work at the frontier of autonomous mobility Own your systems end-to-end, from design to deployment Collaborate with a passionate, tight-knit robotics team See your code power real UGVs in live environments