Machine Learning Engineer

What you'll do:

• Lead ML model lifecycle, from research and experiments to implementation and deployment.
• Build and deploy deep learning models on GCP and edge devices , ensuring real-time inference.
• Combine multiple sensor inputs into powerful multi-modal ML models.
• Implement and refine CNNs, Vision Transformers(ViT) , and other architectures.
• Design sensor-fusion methods for better perception and decision-making.
• Optimize inference for low-latency , efficient production use.
• Work closely with software and hardware teams to bring AI into mission-critical systems .
• Create and scale pipelines for training, validating, and improving models .
• Ensure your models are robust, interpretable, and secure.

What you ll bring:

• 
  Deep expertise in TensorFlow and PyTorch
• .Hands-on experience with CNNs, ViTs, and DL architectures
• .Experience with multi-modal ML and sensor fusion
• .Cloud deployment skills- GCP preferred
• .Edge AI know-how (NVIDIA Jetson, TensorRT, OpenVINO)
• .Proficiency in quantization, pruning, and real-time model optimization
• .Solid computer vision and object detection experience
• .Ability to work with limited datasets (using VAEs or similar) to generate synthetic data , and experience with annotation and augmentation
• .Strong coding skills in Python and C++ , with high-performance computing expertise

.Nice to have

• :2-6 years of relevant experience
• .MLOps experience- CI/CD, model versioning, monitoring
• .Knowledge of reinforcement learning
• .Experience in working in fast-paced startup environments
• .Experience in AI for autonomy, robotics, or UAV systems
• .Knowledge of embedded systems and hardware acceleration for AI