Sigma Computing jobs

CONSULTOR ATENDIMENTO OPERACIONAL SENIOR Sao Paulo - Sigma posted: Posted 30+ Days Ago

Kernel Engineer Bengaluru, Karnataka, India Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize

Analista de Operacoes RE PL Sao Paulo - Sigma posted: Posted Yesterday

Sr. Signal Integrity / Power Integrity Engineer, Annapurna Labs, Machine Learning Hardware Austin, Texas, USA Annapurna Labs (our organization within AWS) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. We are seeking a Senior SI/PI Engineer (Signal Integrity and Power Integrity) who will play a key role in the definition, design and validation of AWS next generation machine learning ASICs. As a senior member of our hardware team, you will have a meaningful opportunity to participate in the design and execution of all SI related topics, with the goal of creating and customized platforms that fit within AWS datacenter's world leading technology. Candidates will be successful in this role with these skills: - Strong communication and teamwork skills, with the ability to interact effectively with cross-functional teams. - Decisive, yet collaborative, approach, balancing technical constraints with business and manufacturing considerations. - Problem-solving mindset, able to troubleshoot and resolve SI/PI-related challenges efficiently. Key job responsibilities - Perform end-to-end high-speed channel simulations to ensure signal integrity across complex designs. - Conduct SI/PI analysis to optimize PCB layouts, minimizing losses and signal degradation. - Utilize simulation tools such as ADS, MATLAB, Cadence, HFSS, and others to evaluate performance and troubleshoot issues. - Work with PCIe protocols

Commercial Paralegal - Contracts Manager New York City, NY About Us: Sigma is a fast-growing startup headquartered in San Francisco and dedicated to revolutionizing data analytics. Our dynamic team thrives on innovation, collaboration, and achieving excellence in everything we do. As we continue to scale, we are seeking an experienced Contracts Manager to support our legal operations and contribute to our company's growth. Key Responsibilities: The contracts & legal operations manager will manage and oversee the full contract lifecycle for commercial agreements while ensuring regulatory compliance and risk mitigation. This role will also maintain our contract database and implement process improvements for contract management workflows. - Contract Management: - Maintain and organize the company's contract database and ensure compliance with contract management policies; - Track contract deadlines, renewals, and obligations in contract management system; and - Provide guidance to business teams on contract terms and company policies. - Legal Support and Legal Operations: - Maintain contract templates and playbooks while identifying opportunities for standardization; - Support General Counsel with a variety of initiatives including tooling selection and RFP, outside counsel selection, patent program management; - Maintain legal & compliance team intranet presence; - Create and maintain operational guides and other content; - Support legal department with contract-related projects and process improvements; - Assist with budget tracking and management; and - Implement processes that allow Sigma to track KPI's and other important metrics for the legal team. - Team Collaboration: - Work closely with internal stakeholders, including finance and operations, to

Software Development Manager, ML Accelerators, AWS Neuron, Annapurna Labs Seattle, Washington, USA AWS Machine Learning accelerators are at the forefront of AWS innovation. The Trainium chip delivers industry-leading ML inference and training performance at the lowest cost in the cloud. This is enabled by edge software stack, the AWS Neuron Software Development Kit, which includes a Machine Learning compiler. The SDK natively integrates into popular ML frameworks, such as PyTorch, JAX and TensorFlow. AWS Neuron is widely adopted by many internal and external customers and partners. Amazon Annapurna Labs drives innovation in silicon and software for AWS, blending cloud-scale impact with world-class engineering talent. Our multidisciplinary team spans silicon design, hardware verification, software, and operations. We operate in large, complex domains with small, agile teams, fostering continuous learning and rapid innovation. With no set blueprint, we thrive on experimentation and offer a uniquely dynamic and enriching environment across a wide range of AWS products and services. Learn more about our history: https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success We are seeking an exceptional Software Engineering Manager to lead portion of our Deep-Learning Backend Compiler team at AWS Neuron. You will manage a team of talented compiler engineers focused on machine learning compiler design and development. In this role, you will drive the design and implementation of ML compiler solutions, develop advanced optimization techniques, lead hardware bring-up for next-generation chips, and influence pre-silicon design decisions while mentoring your team. This position offers the opportunity to directly impact AWS's machine learning infrastructure and accelerate the delivery of innovative

Manager Integrated Lean Six Sigma (IL6S) Monterrey, Mexico posted: Posted 30+ Days Ago

ASIC Engineer II, Cloud-Scale Machine Learning Acceleration team Cupertino, California, USA Utility Computing (UC) 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 security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't

Estágio em Processos Gerenciais - Faturamento Sao Paulo - Sigma posted: Posted 7 Days Ago

Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs Cupertino, California, USA The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology This is an opportunity to work on cutting-edge products at

Lean/Six Sigma Black Belt - Logistics Excellence Mesa, Arizona posted: Posted 24 Days Ago

ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs Cupertino, California, USA The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology This is an opportunity to work on cutting-edge products at the

Lean 6 Sigma Black Belt East Peoria, Illinois posted: Posted 10 Days Ago

ASIC Design Engineer, Cloud-Scale Machine Learning Acceleration team - Annapurna Labs Cupertino, California, USA 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 inference datacenter server. Our success depends on our world-class server infrastructure; we're handling massive scale and rapid integration of emergent technologies. We're looking for an ASIC Design Eengineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs. Key job responsibilities As an ASIC Design Engineer, you will: • Develop and implement high-performance, area and power-efficient RTL designs to meet project specifications and targets • Conduct in-depth analysis of designs, microarchitectures, and architectures to optimize trade-offs between features, power consumption, performance, and area requirements • Create microarchitectures, implement SystemVerilog RTL, and deliver synthesis and timing-clean designs with appropriate constraints • Execute lint and clock domain crossing quality checks to ensure design integrity • Collaborate closely with cross-functional teams, including architects, fellow designers, verification specialists, pre- and post-silicon validation teams, and synthesis, timing, and back-end experts The ideal candidate

Applied Scientist, Edge AI and Science Cambridge, England, GBR Amazon Devices is an inventive research and development company that designs and engineers high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health & Wellness, Amazon Echo, and Astro products. This is an exciting opportunity to bring generative AI to Amazon's consumer products, both on-device at the edge and in the cloud. Our compression platform delivers 20x to 100x neural network compression, but using it well still takes weeks of hands-on learning and expert intuition. The Edge AI Model Studio team exists to change that. We become the expert users so partner teams don't have to: we turn compression science into reliable, production workflows, and we package the results into a library of compression-ready student architectures that partners can run on their own. Our north star is simple. Training-to-deployment should feel like pushing a button, not a month-long science project. We are looking for an Applied Scientist to join Model Studio and help compress the next generation of models for edge and cloud deployment across modalities, including large language models, vision-language models, speech and audio models, and omni models that reason jointly over text, audio, and video. You will apply and extend state-of-the-art compression recipes to real models, define the benchmarks and evaluation methodology that make trade-offs explicit, and build the reference implementations that let other teams deploy compressed models without our help. You will work backwards from deployment constraints such as memory, latency, throughput, power, and cost,

Estágio em Gestão de Capacitação e Métricas Operacionais Sao Paulo - Sigma posted: Posted 15 Days Ago

Continuous Improvement / Lean-6-Sigma Engineer (m/w/d) – Talent Pool Loerrach, Germany posted: Posted 30+ Days Ago

Sr. ASIC Design Engineer, Cloud-Scale Machine Learning Acceleration - Annapurna Labs Austin, Texas, USA Utility Computing (UC) 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 security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is

Service Sales Consultant (Southern Region) Sigma Elevator (M) Sdn Bhd, No.53, Jalan Molek 3/20, Taman Molek, Malaysia posted: Posted 24 Days Ago

C/C++ Hardware / Software Co-Design SDE, Machine Learning Acceleration Systems Austin, Texas, USA 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 an exceptional career opportunity. Join us in shaping the future of AI acceleration At the heart of AWS Machine Learning servers reside our custom Amazon-designed silicon that powers next-generation machine learning capabilities for our customers. We're seeking an experienced C/C++ engineer to join our embedded software team, where you'll develop bare metal firmware that drives neural network model execution across our custom ASIC-based ML Accelerator chips. Working at the intersection of hardware and software, you'll collaborate closely with our architecture and design teams to co-develop the firmware and custom hardware that enables machine learning within our accelerator chips. Our mission is ambitious: to democratize access to industry-leading ML infrastructure and make deep learning capabilities accessible to everyday software developers. From the ground up, you'll help build the foundation that makes this vision possible. the Annapurna Labs team operates with the agility and culture of a startup, but with the full weight of Amazon behind us and

Finance Six Sigma Black Belt, Amazon Customer Excellence Services (ACES) Hyderabad, Telangana, IND Amazon Customer Excellence Services (ACES) team leads the identification and implementation of high-impact initiatives to continuously improve Finance Global Business Services (FGBS) accounts payables operations. Based in Hyderabad, this role drives tangible cost savings initiatives, manages Lean - Six Sigma improvement project portfolios, and fosters an innovative culture while maintaining customer obsession. Key job responsibilities Strategic Leadership • Partner with Learning & Development, Business Analytics, Business Partners and Finance teams to drive process improvements. • Align local and global Amazon Customer Experience Solutions (ACES) initiatives with Financial Global Business Services (FGBS) goals Operational Excellence • Lead continuous improvement projects including Six Sigma, Lean, Kaizen, and Failure Mode Effects Analysis (FMEA) • Mentor team members on improvement projects and Just Do It (JDI) and replication initiatives. • Analyze key process indicators to identify optimization opportunities. • Conduct Gemba Walks to generate improvement ideas. Conduct prioritization sessions with stakeholders to align projects and priorities. Project Management • Guide projects to successful completion through the DMAIC methodology leading or mentorship. • Track and deliver measurable business benefits • Develop and execute site-wide communication strategies Development & Culture • Deliver technical training in Six Sigma, Kaizen, and FMEA methodologies • Foster continuous improvement culture through coaching Problem Solving • Resolve systemic process barriers • Design solutions for complex operational challenges • Prioritize projects based on business impact A day in the life - Mentor Lean / six sigma Belt project and

Senior Revenue Operations Manager New York City, NY Sigma is looking for a Sr. Revenue Operations Manager to sit at the centre of a ~$40M ARR business that is doubling year on year. You will work directly alongside our Area VP of Sales - embedded in the business, not observing it from the outside. This is a role built on trust, proximity, and the ability to shape decisions before they get made. Think less ops coordinator, more trusted advisor with a bias for action and a sharp analytical mind. Someone who has outgrown execution and wants to shape strategy. Someone who gets uncomfortable when they are the last to see a problem coming. Someone who would rather design the system than run the report. What you will own - The operating rhythm of a high-growth sales organisation - QBRs, planning cycles, leadership offsites, and the cadences that keep a fast-moving team aligned. - Annual planning, built from the ground up with sales leadership rather than handed down from on high. You will own the process, the timeline, and the room. - Strategic diagnostics - surfacing the leading indicators, structural risks, and pipeline dynamics that tell us where we are headed before the quarter tells us itself. - AI-native workflows that eliminate grunt work and free up our talent bench to spend time on decisions, not dashboards. - A direct line to senior leadership within the company, with the credibility to challenge as well as advise. You will be expected to

Member of Technical Staff - Applied ML, RecSys Boston, Cambridge, Massachusetts, United States About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. The Opportunity This is a rare chance to apply frontier sequential recommendation architectures to real enterprise problems at scale. You will own applied ML work end-to-end for recommendation system workloads, adapting Liquid Foundation Models for customers who need personalization and ranking capabilities that run efficiently under production constraints. Unlike most recommendation roles that are siloed into a single product surface, this role gives you full ownership over how large-scale recommendation models are adapted, evaluated, and deployed for enterprise customers. Between engagements, you will build reusable applied tooling and workflows that accelerate future delivery. If you care about data quality at scale, user behavior modeling, and making recommendation systems actually work in enterprise production environments, this is the role. What We're Looking For We need someone who: - Takes ownership: Owns customer recommendation system engagements end-to-end, from requirements through delivery and evaluation. - Thinks at scale: Can reason about user interaction data, sequential modeling, feature engineering, and evaluation across large-scale production systems. - Is pragmatic: Optimizes for measurable customer outcomes (engagement, conversion, revenue lift) over theoretical novelty.

AI/ML Specialist Solutions Architect, Retail, AGS US Specialist SA, Retail New York, New York, USA AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and committed support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art genAI/ML tools on Amazon Web Service (AWS)? Come join us! At Amazon, we've been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com's recommendations engine is driven by machine learning, as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition with deep learning; as is Prime Air. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it's a big part of our heritage. Within AWS, we're focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and