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Machine Learning Engineer
1 month ago
Position Summary
The Distributed AI group in SAIC Cambridge is seeking a Machine Learning Engineer to collaborate with research scientists and engineers on diverse skill sets, supporting research efforts in embedded/distributed ML, communications, and robotics. The successful candidate will contribute to internal research tools, help implement and extend research ideas, and realise research prototypes into demos and minimum viable products (MVPs).
Role and Responsibilities
As part of the group, you will contribute to technical and system aspects of deploying embedded/distributed/mobile ML systems for cutting-edge research and real-world applications in vision and language. You will have the opportunity to participate in publishing academic papers and patents, as well as engage in cross-group collaborations and professional growth within the team.
Requirements
The ideal candidate will have a deep understanding of system design and architecture, with exposure to different layers of the system stack and a comprehensive knowledge of how ML systems operate. You should possess an analytical and rigorous approach, making design choices based on quantitative data.
Key Skills and Qualifications
- Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantisation, pruning, sparsification, etc.)
- Experience with deployment on embedded and mobile devices (ML inference and/or training)
- Experience with distributed and multi-GPU training at scale
- Fluency in Python, C/C++, and GNU Linux
- Experience working as a member of a team
Preferred Skills
- Experience in real-world (distributed) system deployment and maintenance
- Hands-on experience and understanding of networking stack and communication protocols (e.g. distributed inference/training over PAN/LAN/WLAN, software defined radio, etc.)
- Experience with practical aspects of deploying computer vision in real-world settings such as AR/VR, smart homes, and robotics (e.g. camera calibration, RGB-D and/or motion-tracking sensors, multi-camera ecosystems, etc.)
- Experience with large-scale NLP research, including discriminative or generative tasks. This includes all steps of the pipeline, from data collection and preprocessing to large model adaptation, fine-tuning, and optimisation.
- Android Operating System and Android app development
- Robot Operating System (ROS)
Contract Type: Permanent
Job Location: Cambridge, UK
Hybrid Working: Standard working week will be 3 days onsite and 2 days working from home if preferred
Employee Benefits: Competitive Salary, Annual Performance Bonus up to 10%, Pension Scheme with company contribution up to 8.5%, Income Protection, Stocks & Shares ISA, Life Assurance, 25 days holiday (increasing to 30 with length of service). We also have a wide range of Flexible Benefits to choose from with Samsung providing an allowance of £600 per year to spend on them.
