Bellatrix Aerospace
Location
Bangalore | India
Job description
Company & Culture: Bellatrix Aerospace is a space transportation company developing new age technologies that shape the future of our industry. We specialize in the development and production of propulsion systems and in-orbit transportation solutions. Our work has won two National Awards and backing of the government and many marque investors. More details of the company are available on –
At Bellatrix, we strive to create an environment that rewards creativity, performance and perseverance. At the same time, we also understand that failures are steppingstones to success on a journey to create something that never existing. In other words, our culture is fueled by intellectual curiosity, and our team takes pride in creating technologies that impact India and the world, growing together and achieving their goals each day. Full Time and onsite at work Location: Bangalore Job Description: Drive innovation in ML optimization, integrating computer vision and multimodal insights for efficient on-device performance. Transform research concepts into real-world advancements with clear industrial applications. Mandatory Skills: Mathematics : Solid foundation in statistics (distributions, hypothesis testing), linear algebra, and calculus Programming: Extensive experience with Python and a strong grasp of scientific computing libraries (scikit-learn, NumPy, Pandas). Frameworks: Expertise in deep learning frameworks like TensorFlow, Pytorch and ONNX. Strong skills in data querying (SQL), exploration, cleaning, preprocessing, and visualization (e.g., using tools like Matplotlib, Seaborn). Software Engineering Principles: Familiarity with version control (Git) and software development practices. Deployment on Edge Devices: Familiarity with concepts like quantization, pruning and knowledge distillation. Good-to-Have Skills: Cloud Computing: Experience with cloud platforms like AWS, Google Cloud, or Azure. Big Data Frameworks: Experience with distributed computing frameworks (Spark, Hadoop, etc.). MLOps: Knowledge of ML model deployment, monitoring, and continuous improvement (CI/CD pipelines). Key Duties and Responsibilities: Design and develop state-of-the-art machine learning models for computer vision applications. Drive innovation in synthetic image generation for increasing sparse dataset. Dive into research and experimentation with cutting-edge deep learning and generative models (GANs, VAEs, etc.) to produce excellent computer vision models. Harness computer vision techniques (object detection, segmentation, tracking) to build powerful models for diverse use cases in space applications. Efficiently preprocess datasets, employ augmentation, and implement smart feature engineering for large-scale visual data. Relentlessly optimize models for performance and scalability using compression, pruning, quantization, and other techniques. Evaluate and benchmark ML frameworks and libraries for generative AI and computer vision projects. Analyze developed computer vision models, applying compression techniques (like quantization, pruning, knowledge distillation) to dramatically reduce their size and computational requirements without sacrificing accuracy. Evaluate edge hardware platforms (e.g., GPUs, TPUs, dedicated accelerators) and select the ideal options for specific use cases and performance targets. Develop robust deployment pipelines ensuring smooth integration of optimized models onto edge devices. Design processes for over-the-air updates and continuous model maintenance. Proficient in model conversion tools and frameworks (e.g., TensorFlow Lite, Open VINO, ONNX Runtime) effectively translating models across platforms. Benchmark, profile, and debug model performance on target edge devices. Find potential bottlenecks and identify further optimization strategies. Design and run test scenarios that mimic real-world conditions where edge devices will operate, considering issues like environmental factors, power consumption, and connectivity. Document the development, ensuring reproducibility and knowledge-sharing within the team. Embrace code reviews and best practices for software development excellence. Education & Experience Bachelor's, Master's, or PhD in Electronics Engineering or Computer Science, Engineering, or a related field with a strong focus on machine learning / artificial intelligence or computer vision. Proven track record of building and shipping generative AI and computer vision solutions. Master of Python and ML libraries like TensorFlow, PyTorch, Keras, and OpenCV. Firm grasp of deep learning architectures and generative models. Expert in computer vision techniques (object detection, segmentation, tracking, image synthesis). Adept at handling large, diverse visual datasets, employing smart preprocessing and feature engineering. Analytical mindset with a knack for innovative problem-solving. Exceptional communicator and collaborator; comfortable working across teams. Solid software engineering understanding (version control, agile methodologies). Familiar with various edge device architectures (ARM, microcontrollers, FPGAs). Passion for research and a desire to contribute to the broader ML community.Job tags
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