Description
InstaDeep, founded in 2014, is a pioneering AI company at the forefront of innovation. With strategic offices in major cities worldwide, including London, Paris, Berlin, Tunis, Kigali, Cape Town, Boston, and San Francisco, InstaDeep collaborates with giants like Google DeepMind and prestigious educational institutions like MIT, Stanford, Oxford, UCL, and Imperial College London. We are a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner. We have been listed among notable players in AI, fast-growing companies, and Europe's 1000 fastest-growing companies in 2022 by Statista and the Financial Times. Our recent acquisition by BioNTech has further solidified our commitment to leading the industry.
Join us to be a part of the AI revolution!
The Role:
We seek a research engineer who can collaborate closely with our research and machine learning engineering teams. You will work at the intersection of cutting-edge research and engineering with an emphasis on scaling machine learning models to leverage large compute clusters and push the boundaries of what is possible. If you enjoy writing highly performant code, find joy in utilising all the FLOPS that the underlying hardware provides, and love diving deep into algorithm optimisation, this is the position for you.
TLDR:
Optimise models and pipelines to run as fast as possible in a distributed setup, taking advantage of the underlying hardware and applying them to some of the most exciting research problems in the industry.
Responsibilities
- Algorithmic Optimisation: Research and understand the latest deep learning literature to implement and optimise state-of-the-art algorithms and architectures, ensuring compute efficiency and performance.
- Scaling Expertise: Design and implement strategies to efficiently scale machine learning models across different accelerator platforms (GPU/TPU).
- Performance Optimisation: Analyse and profile ML systems under heavy load, pinpointing bottlenecks and implementing targeted optimisations.
- Distributed Systems Architecture: Create robust distributed training and inference solutions for maximum computational efficiency.
- Low-Level Mastery: Understand how to take advantage of the underlying hardware. Although not a prerequisite, be comfortable working with technologies like C/C++, XLA, Pallas, Triton, and/or CUDA code to achieve performance breakthroughs.
Required Skills
- A Masters or equivalent in Computer Science, Engineering, Mathematics, or related field.
- 2+ years of work experience.
- Expertise in Python.
- Experience working with Linux systems.
- Experience with Docker and container orchestration.
- Experience with at least one modern machine learning framework (JAX, Tensorflow, PyTorch, etc.)
- Experience with software profiling, identifying bottlenecks, and delivering efficient solutions.
Highly Desirable
- Experience working with JAX and packages within the JAX ecosystem.
- Track record of successfully building and scaling ML models.
- Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.)
- Experience working with HPC clusters and distributing programs over multiple hosts.
- Understanding of GPU/TPU architectures and their implications for efficient ML systems.
- Experience using statically typed languages like C, C++, etc.
- Fundamentals of modern Deep Learning and experience with Reinforcement Learning.
- Actively following ML trends.
What we offer:
- Real-World Impact: Directly contribute to the performance and reach of our AI solutions.
- Cutting-Edge Challenges: Tackle complex problems at the forefront of machine learning and large-scale system design.
- Growth-Oriented Environment: Expand your expertise with a team of talented engineers dedicated to advancing ML scalability.
Our commitment to our people
We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this than by joining our team? We operate on a hybrid work model with guidance to work at the office at least 2 to 3 days per week to encourage close collaboration and innovation. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.
Right to work: Please note that you will require the legal right to work in the location you are applying for.
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