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hackajob is collaborating with Sierra to connect them with exceptional professionals for this role. About us At Sierra, we're creating a platform to help businesses build better, more human customer experiences with AI. We are primarily an in-person company based in San Francisco, with growing offices in Atlanta, New York, London, Paris, Madrid, Munich, Singapore, Japan, and Sydney. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are... more ->
hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. JOB DESCRIPTION Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies. As a Lead Infrastructure Engineer at JPMorgan Chase within the Infrastructure Platforms Team, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Also, you will... more ->
AWS's Trainium and Inferentia chips power the world's largest machine learning clusters. Our team builds virtual platforms - full-system C+ and SystemC models of these custom SoCs - that let software teams start development months before silicon arrives. For Trainium3, our virtual platform enabled running a full training workload within 12 hours of first silicon. We're looking for a software engineer to build and own the models and infrastructure that make this possible. What you'll do: - Build and own functional models of SoC subsystems that integrate into our full-system virtual platform,... more ->
Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. We have data center locations in the U.S., Europe, Singapore, and Japan, and customers across all industries. Custom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team you'll be responsible for the design and optimization of hardware in our data centers including AWS Inferentia, our custom designed machine learning... more ->
The MLIL DataPlane team is looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration. Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.... more ->
AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized... more ->
Annapurna Labs stands at the forefront of hardware/software co-design, leading innovation not just within Amazon Web Services (AWS) but across the entire industry. We design and build every component of our hardware and software to create best-in-class machine learning products that accelerate customer workloads through industry leading hardware using our custom silicon solutions. If you're passionate about building the highest-performing, hardware-accelerated Machine Learning systems and want to be part of the entire journey from pre- through post-silicon development, Annapurna Labs offers... more ->
Every token a large language model generates depends on data reaching the right accelerator at the right moment. As AI models outgrow any single chip, the network between accelerators becomes the bottleneck that decides how fast - and how affordably - the world's largest models can serve real users. That network layer is what our team builds. We're looking for an engineer to work at the frontier of disaggregated inference: splitting LLM serving into separate prefill and decode pools and moving the model's KV cache between them at the limit of what the hardware allows. Get it right and users... more ->
The MLIL DataPlane team is looking for a Senior Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration. Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed... more ->
Custom SoCs (System on Chips) are the brains behind AWS's Machine Learning servers. Our team builds C+ & SystemC functional models of these custom-designed accelerator SoCs for use by AWS internal teams. We're looking for a Senior SoC Modeling Engineer to join the team and deliver new functional models, infrastructure, and tooling for our customers. As part of the ML accelerator modeling team, you will: - Develop and own SoC functional models end-to-end, including model architecture, integration with other model or infrastructure components, testing, and debug - Work closely with... more ->