Job Description

FairAds AI is at the forefront of revolutionizing advertising. We're seeking a highly motivated Machine Learning Engineer / Deep Learning Engineer Intern to join our pioneering team for an immediate start in Mumbai, Maharashtra, India. This is a paid, in-person position . You'll dive deep into developing and deploying, DPDP-compliant ML/DL models for real-time analytics. This is a unique opportunity to work on impactful projects involving Computer Vision, real-time data processing, and privacy-preserving AI. What You'll Help Build & Responsibilities * Develop & Implement ML/DL Models: Design, train, and fine-tune models like YOLO, DeepSORT, and DeepFace for tasks such as impression counting, dwell time analysis, and anonymized demographic analysis. * Advanced Computer Vision Tasks: Apply your OpenCV and CV knowledge for object detection, tracking, pose estimation, and image segmentation on real-world video streams. * Data Preprocessing & Management: Handle raw camera data, including cleaning, annotation, and implementing anonymization techniques (e.g., blurring, feature embeddings) to ensure DPDP Act compliance. Manage datasets using tools like DVC or cloud storage. * Edge Computing & Deployment: Optimize and deploy models on edge devices (e.g., NVIDIA Jetson, Raspberry Pi), managing real-time processing pipelines and considering power/thermal constraints. * Real-Time Analytics: Design streaming data pipelines for video feeds and optimize inference speed (e.g., using TensorRT) to deliver low-latency KPIs. * Privacy by Design: Actively contribute to building privacy-preserving ML pipelines, understanding DPDP Act principles (data minimization, consent, purpose limitation) and implementing secure data handling. * Containerization & CI/CD: Utilize Docker to package and deploy models consistently. Contribute to CI/CD pipelines for automated testing and deployment. Core Technical Skills We're Looking For * Python Programming: Proficiency in Python for ML/DL development, including libraries like PyTorch, TensorFlow, OpenCV, NumPy, Pandas, and Matplotlib. Ability to write modular, reusable code. * Machine Learning & Deep Learning: Strong understanding of supervised/unsupervised learning, neural networks (CNNs), architectures (YOLO, ResNet, ViT), transfer learning, loss functions, optimizers, and regularization. * Computer Vision: Expertise with OpenCV for image/video processing, object detection, tracking, and pose estimation. Experience handling real-time video streams. * Data Preprocessing: Skills in data cleaning, transformation, annotation, and implementing anonymization techniques. Key Domain-Specific & Deployment Skills Needed * Edge Computing: Experience or strong interest in optimizing models (pruning, quantization) for resource-constrained edge hardware (NVIDIA Jetson, Raspberry Pi) and managing real-time edge processing. * Real-Time Analytics: Ability to design streaming data pipelines and optimize for low-latency inference. * Docker & Containerization: Writing Dockerfiles and managing containers for ML model deployment. * Edge Device Deployment: Configuring edge hardware (CUDA, cuDNN), managing cross-compilation, monitoring, and potentially OTA updates. * Version Control & CI/CD (Git, GitHub Actions/Jenkins): Experience with versioning code and models (MLflow, DVC) and automation. * Cloud Integration (Optional but valued): Familiarity with AWS, Azure, or GCP for aggregating anonymized KPIs or model training. API development (Flask/FastAPI) is a plus. Soft Skills for Success * Problem-Solving & Analytical Thinking: Ability to tackle complex challenges in model performance. * Attention to Detail: Meticulous approach to data handling, model accuracy, and compliance requirements. * Pro Vibe Coder: You're someone who can skillfully navigate and debug code, especially code that might have been initially generated or assisted by AI, ensuring its robustness and efficiency. What We Offer * Pioneering Projects: Work on groundbreaking analytics solutions using advanced AI and edge computing. * Hands-on Experience: Gain invaluable experience with the full lifecycle of ML models – from conception to deployment on edge devices. * Mentorship: Learn from experienced professionals in AI, Computer Vision, and privacy-preserving technologies. * Impactful Contribution: Directly contribute to building a more intelligent and compliant ecosystem. Show more Show less