Position Summary

The Distributed AI group in SAIC Cambridge is looking for a Machine Learning Engineer to join the team and work directly with research scientists and ML engineers of diverse skill sets, supporting research efforts in the areas of embedded/distributed ML, communications and robotics. The person will be responsible for contributing to internal research tools, helping implementing/extending research ideas and/or realising 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, with the possibility of partaking in publishing academic papers and patents. Moreover, there is the potential for cross-group collaborations and the ability to learn and grow inside the team. 

To this direction, they are searching for a candidate with deep knowledge in system design and architecture. The candidate should have exposure to different layers in the system stack and spherical knowledge about how ML systems operate. Lastly, the candidate should have an analytical and rigorous approach and make design choices based on quantitative data. In summary, we are searching for a “jack of all trades” in MLSys.

Skills and Qualifications

MS or PhD in CS/EE or equivalent experience in the industry, with key skills:

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 in working as member of a team

Any of the following skills will also be positively considered:

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 to10%, 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.

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