Data Science Lead
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Key skills for this role
About the Role
99brightminds is seeking a Data Science Lead to set technical direction for computer-vision research and lead a team of data scientists and ML engineers.
Key Skills for This Role
Responsibilities
- Lead the design and development of computer vision solutions across object detection, tracking, re identification, action recognition, and segmentation
- Drive model selection and experimentation with YOLO, Transformer based / ViT architectures, and RF DETR
- Apply and guide the use of Vision Language Models (VLMs), including fine tuning for computer vision tasks
- Own model optimisation for production (TensorRT, ONNX, OpenVINO), accounting for edge AI deployment constraints
- Architect and oversee multi camera tracking and video analytics systems
- Own the MLOps lifecycle end to end — training, deployment, and monitoring
- Lead, mentor, and conduct code reviews for a team of data scientists and engineers
- Contribute to solution architecture and communicate technical direction and outcomes to stakeholders
Requirements
- Bachelor's or Master's degree (PhD a plus) in Computer Science, Machine Learning, Data Science, or a related field
- 10 – 15 years of applied machine learning experience, with deep expertise in computer vision
- Strong Python, with hands on PyTorch / TensorFlow
- Hands on experience with YOLO, Transformer based / ViT architectures, and RF DETR
- Experience with Vision Language Models (VLMs) and fine tuning for CV tasks
- Proven model optimisation experience (TensorRT, ONNX, OpenVINO) and understanding of edge AI deployment constraints
- Experience building multi camera tracking and video analytics systems
- Command of the full MLOps lifecycle (training → deployment → monitoring)
- Demonstrated team leadership, code review, and mentoring
- Strong stakeholder communication and solution architecture skills
Full Job Posting
Position Summary
- As Data Science Lead, you will set the technical direction for AIQ's computer vision research and own the quality of the models that power our video analytics platform.
- You will lead a team of data scientists and ML engineers from problem framing through to production and monitoring, while shaping solution architecture and communicating outcomes to stakeholders.
Responsibilities
- Lead the design and development of computer vision solutions across object detection, tracking, re identification, action recognition, and segmentation.
- Drive model selection and experimentation with YOLO, Transformer based / ViT architectures, and RF DETR.
- Apply and guide the use of Vision Language Models (VLMs), including fine tuning for computer vision tasks.
- Own model optimisation for production (TensorRT, ONNX, OpenVINO), accounting for edge AI deployment constraints (latency, FPS, GPU limits).
- Architect and oversee multi camera tracking and video analytics systems.
- Own the MLOps lifecycle end to end — training, deployment, and monitoring.
- Lead, mentor, and conduct code reviews for a team of data scientists and engineers.
- Contribute to solution architecture and communicate technical direction and outcomes to stakeholders.
Qualifications
- Bachelor's or Master's degree (PhD a plus) in Computer Science, Machine Learning, Data Science, or a related field.
- 10 – 15 years of applied machine learning experience, with deep expertise in computer vision.
- Strong Python, with hands on PyTorch / TensorFlow.
- Hands on experience with YOLO, Transformer based / ViT architectures, and RF DETR.
- Experience with Vision Language Models (VLMs) and fine tuning for CV tasks.
- Proven model optimisation experience (TensorRT, ONNX, OpenVINO) and understanding of edge AI deployment constraints (latency, FPS, GPU limits).
- Experience building multi camera tracking and video analytics systems.
- Command of the full MLOps lifecycle (training → deployment → monitoring).
- Demonstrated team leadership, code review, and mentoring.
- Strong stakeholder communication and solution architecture skills.
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