Sr. Computer Vision & AI Engineer

Key ResponsibilitiesDesign & Implement Computer Vision Solutions: Develop and optimize end-to-end computer vision pipelines using advanced deep learning techniques.LLMs-VLMs: Have awareness about the latest technologies in the field of LLMs and VLMs. Model Development & Deployment: Build, train, and deploy deep learning models (e.g., object detection, image segmentation, classification) using frameworks like PyTorch and TensorFlow.Data Pipeline & Infrastructure: Work closely with data engineers to ensure efficient data preprocessing, augmentation, and real-time inference pipelines.Docker & REST APIs: Containerize applications for scalable deployments and create robust RESTful APIs for seamless integration with other services.UI Development (PyQt): Develop or integrate user interfaces for internal tools or customer-facing applications.Model Monitoring & Experiment Tracking: Leverage tools like Weights & Biases (wandb) or MLflow to track experiments, monitor model performance, and ensure continuous improvement.Performance Optimization: Conduct performance tuning and hardware optimization (GPU/CPU) to achieve high throughput and low latency.Collaboration & Mentorship: Work in cross-functional teams (Product, Data, DevOps) and mentor junior developers on best practices and new technologies.Required Qualifications5+ years of hands-on experience in Computer Vision and Deep Learning.Fluency in Python; additional programming languages (C++, Java, etc.) are a plus.Expertise in Deep Learning Frameworks: PyTorch and TensorFlow.Proficiency with Docker for containerization and microservices.Experience with RESTful API design and implementation.Knowledge of PyQt (or similar frameworks) for desktop UI development.Familiarity with Model Monitoring & Experiment Tracking (Weights & Biases, MLflow, etc.).Strong background in linear algebra, calculus, and probability/statistics as they relate to ML.Excellent problem-solving and debugging skills.Bachelor’s/Master’s/PhD in Computer Science, Electrical Engineering, or a related field (or equivalent work experience).Preferred Skills & Nice-to-HavesExperience with DevOps practices (CI/CD, Kubernetes).Familiarity with Cloud Platforms (AWS, Azure, GCP) for model deployment and scaling.Understanding of Edge Computing and on-device model optimization (TensorRT, ONNX).Knowledge of NVIDIA CUDA for GPU acceleration.WANDB and MLflow for training monitoring.Contributions to open-source computer vision or deep learning projects. What We OfferCompetitive CompensationFlexible Work Arrangements (Remote) and a positive work-life balance.Growth Opportunities: A chance to lead cutting-edge projects and mentor junior developers.Collaborative Culture: Work alongside passionate professionals in an environment that values innovation and continuous learning.