Internship Overview Join us as an AI Developer Intern to gain hands-on experience in building and deploying computer-vision and LLM-based solutions. You’ll work alongside senior engineers to develop object detection/tracking models (LLM, YOLOv8/11), assist with face-recognition pipelines, and help maintain our GPU-powered servers. What You’ll Do Assist in data collection, annotation, and preprocessing for video datasets. Train and fine-tune YOLOv8/11 models under mentor guidance. Prototype face-recognition solutions using pre-trained LLM embeddings. Help deploy models on Linux servers; learn SSH, Docker, and GPU setup. Participate in code reviews, stand-ups, and technical brainstorming sessions. What We’re Looking For Currently pursuing a B.Tech/M. Tech in CS, EE, AI, or related field, or graduated Solid foundation in Python, with coursework or projects using PyTorch/TensorFlow. Basic understanding of computer-vision concepts (object detection, tracking, face recognition). Familiarity with the Linux command line and SSH. Eagerness to learn GPU computing and server management. Strong problem-solving skills and the ability to work in a team. What You’ll Gain Real-world experience deploying AI solutions end-to-end. Mentorship from senior AI engineers. Exposure to GPU infrastructure and MLOps practices. Opportunity to contribute to production-grade code. Letter of recommendation and potential for a full-time offer. Job Types: Full-time, Permanent Pay: ₹10,000.00 - ₹15,000.00 per month Benefits: Flexible schedule Paid sick time Paid time off Provident Fund Schedule: Day shift Fixed shift Supplemental Pay: Performance bonus Yearly bonus Ability to commute/relocate: Mumbai, Maharashtra: Reliably commute or planning to relocate before starting work (Preferred) Experience: AI: 1 year (Preferred) Willingness to travel: 100% (Preferred) Work Location: In person
We’re looking for an experienced AI Developer to join our team and drive the design, development, and deployment of advanced computer-vision and LLM-based solutions. You’ll build real-time object detection & tracking pipelines (LLM, YOLOv8/11), develop face-recognition models on video feeds with LLM support, and manage GPU-powered server infrastructure end-to-end. Key Responsibilities Model Development & Optimization Design, train, and fine-tune LLMs, YOLOv8/11 models for multi-class object detection. Implement face-recognition pipelines leveraging state-of-the-art LLMs and embedding techniques. Optimize inference speed and accuracy for real-time video processing on GPUs. Video Analytics & Tracking Develop multi-camera object-tracking algorithms across disparate video sources. Integrate OpenCV, DeepSORT (or similar), and custom tracking logic for robust performance. Infrastructure & Deployment Provision and maintain Linux servers with SSH, Docker, and GPU drivers (NVIDIA CUDA/cuDNN). Automate CI/CD pipelines for model training, evaluation, and deployment. Monitor GPU utilization, troubleshoot performance bottlenecks, and ensure high availability. Collaboration & Documentation Work closely with product managers, data engineers, and front-end teams to integrate AI services via REST/gRPC APIs. Write clear technical documentation, API specs, and best-practice guides. Required Qualifications Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field. 2-3+ years hands-on experience with: YOLOv8 or YOLOv11 (training, inference, transfer learning) Face recognition frameworks (InsightFace, FaceNet, ArcFace) and LLM embeddings (e.g., Hugging Face Transformers) Python ecosystem: PyTorch/TensorFlow, OpenCV, NumPy, scikit-learn Strong Linux skills: server provisioning, SSH, shell scripting. Proficiency in managing GPU servers (NVIDIA CUDA, Docker GPU containers) Experience deploying models in production (AWS/GCP/Azure or on-prem clusters). Preferred Qualifications Familiarity with video-streaming protocols (RTSP/WebRTC). Knowledge of microservices architecture and API gateways. Exposure to MLOps platforms (MLflow, Kubeflow). Strong debugging, profiling, and performance-tuning abilities. Job Types: Full-time, Permanent Pay: ₹800,000.00 - ₹1,200,000.00 per year Benefits: Flexible schedule Paid sick time Paid time off Provident Fund Location Type: In-person Schedule: Fixed shift Ability to commute/relocate: Mumbai, Maharashtra: Reliably commute or planning to relocate before starting work (Preferred) Experience: AI: 2 years (Preferred) Work Location: In person Speak with the employer +91 9830000000