We're seeking a senior software engineer to join our team and lead the design and development of our Kubernetes-native inference platform. As a senior engineer, you will be responsible for leading design reviews, driving architecture, and ensuring the reliability and scalability of our platform.
\nKey responsibilities include:
\nWe're looking for someone with strong coding skills in Python or Go, deep familiarity with networked systems and performance, and hands-on experience with Kubernetes at production scale. If you have experience with inference internals, batching, caching, mixed precision, and streaming token delivery, that's a plus.
\nIn addition to a competitive salary, we offer a range of benefits including medical, dental, and vision insurance, company-paid life insurance, and flexible PTO. We're committed to creating a work environment that's inclusive, diverse, and supportive of our employees' well-being.
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\nKey responsibilities include:
\nRequirements include:
\nPreferred qualifications include contributions to inference frameworks, experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies, and leading multi-team initiatives or partnering with customers on mission-critical launches.
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\nYou will be responsible for shaping customer-facing capabilities while designing for scalability, extensibility, and performance of GPU training and adjacent areas. This will involve collaborating closely across the platform, product, infrastructure, and research organisations.
\nKey responsibilities include:
\nWe are looking for someone with 8+ years of software engineering experience, with 3+ years in engineering management. You should have a track record of building and operating managed GPU training infrastructure at scale, as well as deep familiarity with distributed training frameworks and parallelism strategies.
\nIn addition, you should have experience with training resilience patterns, such as checkpointing, elastic training, and automated failure recovery for long-running jobs. You should also have a strong understanding of GPU performance fundamentals, including NCCL, interconnect topologies, and memory optimisation.
\nExperience building platform products with clear SLAs is also essential, as is strong cross-functional leadership across platform, product, and research teams. Excellent collaboration and communication skills are also required.
\nThe pay range for this role is $228,600-$314,250 USD per year, depending on location. The total compensation package may also include eligibility for annual performance bonus, equity, and benefits.
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