Sr. Data Science Engineer

Must have skills required :

CNNs, Computer Vision, Vision Transformers, Machine Learning, Python

Good to have skills :

Ci/Cd Pipelines, Edge Computing, AWS, Azure, GCP

Radius AI (One of Uplers' Clients) is Looking for:

Sr. Data Science Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.

Role Overview Description

We are looking for a Sr. Data Science Engineer with deep expertise in computer vision and applied machine learning. This role is central to designing, building, and deploying intelligent vision systems using the latest methodologies and incremental learning strategies. As a data scientist at RadiusAI, you will collaborate closely with engineers and product stakeholders to transform large volumes of image and video data into real-world, high-impact AI applications.

Key Responsibilities

• Design and develop machine learning models for computer vision tasks including object detection, classification, tracking, and scene understanding.
• Lead end-to-end model lifecycle: data preprocessing, feature engineering, model selection, training, evaluation, and deployment.
• Implement and experiment with state-of-the-art techniques including Vision Transformers (ViT) and class-incremental learning for continuous adaptation in production environments.
• Analyze data from edge devices and physical environments to generate actionable insights.
• Develop and maintain reproducible research pipelines using versioned data and experiment tracking tools.
• Collaborate with the ML Ops and engineering teams to ensure seamless integration of models into production environments.
• Optimize models for real-time inference performance, accuracy, and scalability on edge devices or cloud-based infrastructure.
• Document findings, present insights to cross-functional teams, and contribute to technical decision-making.
• Mentor junior data scientists and contribute to team knowledge sharing.

Required Qualifications

• 4+ years of experience in data science or machine learning roles, with hands-on production experience.
• Expertise in computer vision algorithms and deep learning models.
• Strong grasp of cutting-edge architectures such as CNNs, Vision Transformers (ViT), and knowledge distillation techniques.
• Practical experience with class-incremental learning, transfer learning, and domain adaptation.
• Proficiency in Python and ML libraries such as PyTorch, TensorFlow, scikit-learn, and OpenCV.
• Hands-on experience with data versioning and experiment tracking tools such as DVC, MLflowetc.
• Solid understanding of ML model deployment and lifecycle management. ¢ Strong experience in working with structured and unstructured data, especially large-scale image/video datasets.
• Excellent analytical skills and the ability to interpret complex data and communicate results clearly.

Preferred Qualifications

Prior experience in startup or high-growth environments where adaptability is key. ¢ Experience working with cloud platforms such as AWS, GCP, or Azure for scalable ML workflows.

Familiarity with edge computing, real-time inference, and model optimization frameworks like TensorRT, ONNX, or OpenVINO.

Experience with CI/CD pipelines for ML projects and collaboration with ML Ops teams. ¢ Domain knowledge in retail, healthcare, logistics, or behavioral analytics is a strong plus. ¢ Contributions to open-source ML projects or published research papers. ¢ Comfort with visualization tools and reporting frameworks for data storytelling.