Envision For Good

Job Description: Computer Vision Data Scientist (Mid-Level) Location: Bengaluru, India (Hybrid/On-site) About the Role Envision for Good Technologies is a next gen start up with the core ethos of creating ML and Computer Vision based automation solutions for Indian manufacturing and processing industry, building an ecosystem of robust, reliable and scalable technology. We are seeking a Computer Vision Data Scientist (Mid-Level) to join our growing AI team. The ideal candidate will have hands-on experience in designing, training, and deploying deep learning models for object identification, tracking movements & anomaly detection in industrial or real-world environments. You will collaborate with engineers, product managers, and domain experts to build scalable solutions that bridge cutting-edge research with commercial applications. Key Responsibilities Develop and optimize object detection and counting models using deep learning frameworks (e.g., PyTorch, TensorFlow). Work with large-scale image/video datasets: preprocessing, augmentation, annotation, and quality assurance. Implement and fine-tune state-of-the-art architectures (YOLO, Faster R-CNN, LSTM, U-Net, etc.). Deploy models into production pipelines with attention to latency, accuracy, and scalability . Collaborate with cross-functional teams to translate business requirements into technical solutions. Conduct experiments, benchmark models, and document results for stakeholders. Contribute to research and stay updated on the latest advancements in computer vision and AI. Technical Skills & Qualifications Education : Bachelors/Masters in Computer Science, Data Science, Electrical Engineering, or related fields. Experience : Around 10 years of overall experience in the field of data science of which a minimum of 36 years of professional experience in computer vision or applied machine learning related roles. Core Skills : Strong knowledge of object detection, tracking, and counting algorithms . Proficiency in Python and libraries such as OpenCV, NumPy, Pandas, scikit-learn. Hands-on experience with deep learning frameworks : PyTorch, TensorFlow, Keras. Familiarity with annotation tools (LabelImg, CVAT, Roboflow) and dataset preparation. Experience with model deployment (ONNX, TensorRT, Docker, REST APIs). Knowledge of MLOps practices : version control (Git), experiment tracking (MLflow, Weights & Biases), CI/CD pipelines. Exposure to cloud platforms (AWS, GCP, Azure) and GPU acceleration. Preferred Skills : Experience with edge deployment for industrial automation (Jetson, Raspberry Pi, Coral TPU). Understanding of statistical methods for error analysis and performance metrics. Familiarity with Indian industrial automation context (manufacturing, logistics, retail). Soft Skills Strong analytical and problem-solving mindset. Ability to communicate technical concepts to non-technical stakeholders. Collaborative team player with adaptability in fast-paced environments. Curiosity to explore new methods and continuously improve solutions. Proven track record of problem-solving and thought leadership Career Growth This role offers exposure to real-world industrial AI applications in India , opportunities to lead projects, and a pathway to senior roles within the organization as we create a marquee position for ourselves in the emerging domains of computer vison industry. We are passionate about everything we do at EyeForGood Technologies with people as our core strength. We understand and recognize the importance of teamwork, creating a platform for resource upskilling, collaboration and blending the individual contributions. Selection Interested candidates can submit their resumes via email and we will follow up with screening and a 3-stage interview process (2 rounds of technical evaluation, 1 round with HR) for selection. What we Offer Opportunity to work on cutting-edge computer vision problems for real time applications A collaborative, innovation-driven culture with room to experiment and grow Competitive salary & performance-based incentives Exposure to end-to-end product development from research to deployment Flexible work arrangements (hybrid model) and supportive team environment