Software Engineer, Machine Learning - AI Application Engineering [Norway]

 

The HEART AI Application Engineering team’s mission is to explore, develop and help productize high-performance software and hardware technologies for AI at datacenter scale. We achieve this via concurrent design and optimization of many aspects of the system such as models, algorithms, performance, and AI hardware including compute and networking. In essence, we drive the AI HW roadmap at Meta and ensure our existing and future AI workloads and software are well optimized and suited for the hardware infrastructure.We’re a diverse group of problem solvers driven by a culture of experimentation and innovation. As a Software Engineer (SWE), you will be a key member of a team of innovators, working on leading AI workloads, distributed systems, and developing architecture to enable the future of AI.

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Software Engineer, Machine Learning - AI Application Engineering Responsibilities:

• Support projects that accelerates ML applications to best exploit modern accelerator architectures (distributed homogeneous/heterogeneous clusters, multi-core CPUs, FPGAs and GPUs), optimizing training and/or inference of next gen AI workloads here at Meta
• Work towards long-term ambitious software goals, while identifying intermediate milestones
• Develop and collaborate on software projects with other researchers and engineers across diverse disciplines.
• Collaborating with AI research scientists to accelerate the next generation of deep learning models such as Recommendation systems, Generative AI, Computer vision, NLP etc.
• Communicate progress and results.

Minimum Qualifications:

• Strong experience in one or more of High-Performance Computing, AI/ML, Performance and AI hardware including compute and networking or some experience if you have a PhD
• Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, artificial intelligence, or related technical field
• Experience with developing machine learning models at scale from inception to deployment
• Experience or knowledge in developing and debugging in C/C++, Python and/or PyTorch
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

• PhD in Computer Science or a related STEM field.
• Strong knowledge of Computer Architecture and Distributed systems with interest in one or more of High Performance Computing, Machine Learning Models, Performance and AI hardware with emphasis on compute and networking.
• Experience working with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT
• Experience in system performance optimizations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilization analysis and associated tooling development.
• Experience communicating research for public audiences of peers.

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