Adithya Balaji-Robotics and Edge AI Engineer
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Experience
Edge AI Software Engineer
Neura Robotics GmbH
- Deployed and optimized Vision-Language-Action (VLA) and diffusion policy models on NVIDIA Jetson Orin and Jetson Thor, meeting real-time inference latency targets for humanoid robot control loops.
- Built TensorRT engine pipelines (PyTorch → ONNX → TensorRT) with INT8/FP8 post-training quantization, calibration dataset design, and quantization-aware validation, reducing inference memory footprint by over 3× on Jetson without accuracy regression.
- Developed custom CUDA C++ plugins and CUDA Graphs for latency-deterministic, real-time policy execution – meeting hard runtime and memory constraints on embedded GPU targets.
- Developed an inference engine for VLA models on top of llama.cpp bringing different VLA policies under single runtime, packaging each as a single self-contained GGUF that needs no Python or PyTorch.
- Profiled and tuned GPU execution using NVIDIA Nsight Systems and Nsight Compute, identifying CUDA kernel bottlenecks, memory bandwidth saturation, and SM occupancy issues across Jetson Orin and Thor compute profiles for cross-layer performance optimization.
Embedded AI Software Engineer
Huber Automotive AG
- Architected and benchmarked embedded AI inference pipelines on the NXP S32V234 vision processor and constrained microcontroller targets, evaluating optimization strategies for real-time on-device perception under strict power and memory envelopes with no GPU acceleration.
- Developed quantized (INT8) human and object detection models for embedded deployment, applying structured sparsity and token pruning to transformer-based detectors to meet hard compute and memory limits on microcontroller-class hardware.
- Developed embedded AI applications for intelligent battery management (ESP32, Infineon AURIX™ TC3xx/TC4xx) for SOC/SOH estimation, requiring hardware/software co-design across constrained microcontroller targets.
- Built multi-modal sensor fusion pipelines (camera, radar) in C++ and Python with ROS2 for autonomous mobility and target-tracking on embedded platforms.
- Contributed to the VeoPipe project with Fraunhofer IPA, building a certifiable, reproducible MLOps pipeline with standardized testing and traceability for embedded robotics deployment across diverse accelerator targets.
AI Research Intern
Reliev
- Conducted an extensive literature review on multimodal biosignal analysis and deep learning architectures for seizure and motion detection.
- Designed and trained deep learning models for biosignal and motion pattern recognition using CNNs and RNNs on ECG and IMU data.
- Built end-to-end data ingestion and preprocessing pipelines (FastAPI, InfluxDB) for signal fusion, noise filtering, and active learning.
Data and Automation Engineer
EMIS Health
- Developed Machine Learning models to analyze speech input of emergency calls for NHS, United Kingdom.
- Worked on design and development of DataLake on Starburst and AWS with Big Data technologies such as Apache Spark, Kafka, and Airflow, Presto and also databases such as SQL Server, Postgres, Presto, and DynamoDB.
- Developed and implemented QA automation tests utilizing FlaUI, xUnit, Specflow, and Cucumber with C# for .NET applications
Associate Software Engineer
Accenture
- Conducted analysis of large-scale telecommunications data utilizing Data Warehousing and ETL techniques.
- Created automation frameworks using Python and Selenium to increase testing efficiency and accuracy.
- Experience with various tools such as Splunk, Tableau, etc., for data visualization and analysis purposes.
Industry Experience
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Experienced in Healthcare, Manufacturing, Automotive, Information Technology, Biotechnology, and Telecommunication.
Business Area Experience
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Experienced in Information Technology, Quality Assurance, Product Development, Research and Development, and Business Intelligence.
Summary
Robotics and Edge AI engineer building perception and inference systems for real-time autonomy under tight compute, power, and memory constraints. Experienced across the full model lifecycle, from architecture and compression through on-device deployment, with a systems-level focus on reproducibility, reliability, and hardware/software co-design.
Skills
- Programming Languages: Python, C, C++, C#, Matlab
- Skills: Robotics, Ai, Computer Vision, Motion Planning, 3d Reconstruction, Embedded Development, Edge Ai, Qa, Latex And Unit Testing
- Middleware: Ros 1&2, Fastdds, Zenoh, Micro-Ros
- Frameworks: Tensorflow, Pytorch, Caffe, Onnx, Opencv, Pcl, Tensorrt, Ggml, Llama.Cpp
- Deployment: Docker, Kubernetes, Fastapi, Plotly, Dash, Streamlit
- Edge Devices / Hardware: Nvidia Jetson Orin, Nvidia Thor, Nvidia Drive Agx, Nxp S32, Qualcomm Snapdragon, Infineon Aurix™ Tc3xx/Tc4xx
- Devops: Gitlab, Github Actions, Azure Devops, Ci/Cd Pipelines
- Project Management: Jira, Confluence, Polarion, Hp Alm
Languages
Education
Ecole centrale de Nantes
Control and Robotics - Advanced Robotics · France
Anna University
Automotive Engineering · India
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Experience
Global Experience
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