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About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The AI Platform Engineer builds and operates the machine learning and generative AI platform used by teams across Abbott Cancer Diagnostics. You'll own the full model lifecycle in production — data and feature pipelines, training and experimentation, evaluation and promotion, serving, and monitoring — along with the platform services, compute and tooling underneath it. This is hands-on infrastructure work backed by solid platform engineering practice: making inference fast and cheap, making the path from experiment to production repeatable and auditable, and shipping interfaces other engineers can build on — in support of software that ultimately reaches patients. Essential Duties Include, but are not limited to, the following: Build and maintain data, feature, and training pipelines for ML and LLM workloads — ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model. Implement automated evaluation and promotion gates — performance benchmarks, regression checks, and validation criteria that determine whether a model advances toward production. Automate the model lifecycle end to end through CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback. Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling,

Location: San Francisco, CA (Hybrid) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role We're seeking an experienced Senior Optimization Engineer to join our Data Science Team. In this role, you will lead the design, development, and deployment of optimization models that power our software platform across applications including electricity markets, renewable energy, and battery energy storage systems. You will be responsible for developing production-grade optimization engines that solve complex operational and planning problems at scale. This role requires deep expertise in mathematical optimization, strong software engineering skills in Python, and experience building optimization models that integrate with production systems. The ideal candidate has significant experience in the energy industry, particularly electricity markets and battery storage optimization. This position emphasizes technical leadership, ownership of complex optimization projects, and collaboration across engineering, product, and commercial teams to deliver high-impact optimization solutions. Key Res

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. AI at Brex AI Engineering at Brex is redefining how businesses run their finances by building intelligent, autonomous systems directly into the Brex platform. Our teams develop AI agents that don’t just surface insights—they take action, optimizing spend, managing workflows, and making real-time decisions on behalf of our customers. By deeply integrating proprietary financial data with product and platform infrastructure, we’re turning complex financial operations into simple, automated experiences and setting a new standard for how modern finance works. What you’ll do You'll be a product engineer building Brex's Audit Agent — an agentic system that reviews customer spend at scale and replaces the manual work traditionally done by BPO teams. The agent itself reasons; the surrounding product harness is what makes that reasoning useful, trustworthy, and operable for real customers. That product harness is where you'll live. You'll desig

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking an experienced Principal Hardware Diagnostics Engineer to design and develop diagnostics software used to monitor hardware health and diagnose system-level issues across Graphcore’s AI infrastructure platforms. This role focuses on building diagnostics agents, tools, and analytics frameworks that enable engineers and automation systems to identify, isolate, and resolve hardware issues across blade-level servers and rack-scale clusters. The Team Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. The Systems Engineering and Platform Validation team ensures Graphcore’s AI compute platforms are reliable, diagnosable, and operationally robust at scale. The team co

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Responsibilities and Duties We are seeking a highly skilled System Tests & Diagnostics Engineer to develop, extend, and integrate specialized silicon validation and diagnostics tools for next-generation AI SoCs. Unlike traditional validation roles focused on executing test plans, this position is responsible for developing the diagnostic software and stress tools that expose hardware failures, characterize silicon behavior, and improve platform observability throughout bring-up and validation. You will work closely with Arm engineers to understand and extend existing diagnostics technologies while developing Graphcore-specific capabilities for future AI hardware. Role Summary You will work with existing Arm-developed diagnostics technologies and extend them to support Graphcore's next-generation AI silicon. You will be responsible for developing system-level diagnostics and stress tools that integrate with an existing framework to detect data integrity, computational correctness, performance, and reliability issues across CPUs, AI accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Examples include silent data corruption (SDC) tests, power transient stress tools, and platform diagnostics, with opportunities to develop new diagnostics as future hardware capabilities evolve. This role requires close collaboration with hardware architects, firmware enginee

We are expanding our agentic AI capability and are looking for an AI Engineer to join the team. You will work alongside senior engineers to build and maintain AI systems — contributing to agentic pipelines, retrieval infrastructure, and the integrations that tie these systems together. This is a hands-on implementation role with real ownership of components. You will grow your skills in a fast-moving AI practice, working on production systems that directly affect client outcomes. What This Involves: Build and maintain agentic pipelines and workflows under the guidance of senior engineers: tool use, orchestration, and multi-step reasoning. Implement and tune RAG pipelines — including embedding, chunking strategies, vector retrieval, and retrieval evaluation. Contribute to memory and context layer components: integrating vector databases, supporting knowledge graph pipelines, and helping maintain state management across agentic systems. Write clean, well-tested Python code and participate in code reviews. Debug and improve existing AI systems based on evaluation results and production feedback. Collaborate with data engineers and domain experts to integrate AI components with upstream data sources and downstream applications. Document implementations clearly and contribute to shared internal tooling. Requirements: 2–4 years of software or ML engineering experience, with at least 1 year working with LLMs or AI systems in a professional setting. Working knowledge of LLM APIs (OpenAI, Anthropic, or similar) and at least one agentic or RAG framework (LangChain, LlamaIndex, or equivalent). Solid Python skills and comfort with software engineering basics: version control, testing, REST APIs. Familiarity with vector databases or embedding-based search. Curiosity about agentic AI — you follow developments in the space and are eager to apply new techniques. Excellent communication and collaboration skills — comfortable working across cross-functional and client-facing te

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

We are seeking a Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maint