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 Team
Efficiently training machine learning algorithms at scale requires solving novel system problems. Our team leads the design and implementation of high-performance solutions to seamlessly scale our AI systems, including our latest foundation models in biology and beyond. We optimise throughput, scalability, and robustness in some of the largest distributed ML systems, making ambitious research ideas a practical reality.
The Role
We're looking for a Lead Machine Learning Engineer to take charge of tackling performance bottlenecks and lead the development of solutions that scale machine learning to the next level. In this role, you’ll collaborate with a team of software and performance engineers to build systems that enable the next generation of our research. Strong candidates will have demonstrated expertise in managing and executing complex ML system solutions, coupled with a drive to optimise performance and scalability in state-of-the-art workloads.
Responsibilities
- Technical Leadership: Define the long-term technical roadmap and drive the development of scalable, high-performance ML systems.
- Algorithm Optimisation: Optimise state-of-the-art algorithms and architectures from the latest deep learning research for compute efficiency and performance.
- System Scaling: Design strategies for scaling machine learning models across diverse hardware platforms (GPU/TPU) and optimising system performance under heavy load.
- Low-Level Optimisation: Write efficient Python, C/C++, XLA, Pallas, Triton, or CUDA code to achieve performance breakthroughs.
- ML Systems Design: Architect robust distributed systems for training, deployment, and monitoring, ensuring computational efficiency and scalability.
- Data Pipeline Automation: Develop automated pipelines for data processing, model training, validation, and deployment, enabling efficient handling of large datasets.
- Team Collaboration: Partner with research, applied, and product teams to build a cohesive software stack supporting key projects.
- Mentorship: Guide and mentor the ML engineering team, fostering best practices in coding, testing, and documentation.
Required Skills
- Expertise with Python and/or C/C++
- Understanding of Linux systems, performance analysis tools, and hardware optimisation techniques.
- Development with machine learning frameworks (JAX, Tensorflow, and/or PyTorch)
- Passion for profiling, identifying bottlenecks, and delivering efficient solutions.
- Fundamentals of modern Deep Learning
Desired Skills
- Track record of successfully scaling ML models.
- Experience writing custom CUDA kernels or XLA operations.
- Understanding of GPU/TPU architectures and their implications for efficient ML systems.
Representative projects
- Profile algorithm, identifying opportunities for custom XLA/CUDA kernels.
- Implement SOTA architectures (MAMBA, Griffin, Hyena) to research and applied projects.
- Adapt algorithms for large-scale distributed architectures across HPC clusters.
What we offer
- A chance to lead and grow a team of talented engineers in solving some of AI’s most challenging system problems.
- Hands-on experience optimising large-scale distributed ML systems that underpin industry-leading research;
- A front-row seat to the evolution of AI, with opportunities to shape its direction through technical innovation and leadership.
TLDR: Lead a team of engineers to design and implement innovative engineering solutions for scaling ML systems, enabling InstaDeep’s most ambitious AI research.
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 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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