Software Reliability Engineer Jobs

Who we are Graviton Research Capital is a privately funded quantitative trading firm. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Role Overview We are looking for a Program Manager who thrives at the intersection of rigorous engineering and predictable delivery. You will not just "manage tasks" — you will orchestrate the development lifecycle for mission-critical systems. Your goal is to ensure that our elite engineering teams can focus on high-performance code while you own the execution strategy, dependency mapping, and release discipline. Key Responsibilities Lead Agile ceremonies (Sprint Planning, Stand-ups, Retrospectives) tailored for deep-tech engineering teams. Transform high-level trading requirements into granular, executable backlogs. Own capacity planning and burn-down metrics to provide high-visibility delivery timelines. Navigate the complex interplay between engineering teams (e.g., Connectivity, Core Infrastructure, Simulation) to prevent bottlenecks. Build and maintain advanced Jira dashboards, automated roadmaps, and Confluence documentation that serve as the "single source of truth" for stakeholders. Proactively identify technical debt, architectural blockers, or resource gaps that threaten release stability. Continuously refine Agile methodologies to suit low-latency, performance-sensitive development cycles (where "Definition of Done" includes rigorous performance benchmarking). Eligibility & Required Skills 5+ years of experience as a TPM, Program Manager, or Scrum Lead in a product-engineering environment (HFT, FinTech, Networking, or Kernels/Systems). A strong grasp of the software development lifecycle for high-performance systems. While you won't write code, you must understand concepts li

Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition, to statistical inference analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets. Description Lead research in applying machine learning to a wide variety of datasets and trading problems Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure Develop scalable pipeline for building predictive models across global markets Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++ Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research Qualifications Masters or PhD in Computer Science, Mathematics, Statistics, or a related field At least two years of demonstrated experience of ML/AI research in a professional setting or at a repu

Position Overview Diligent is looking for an experienced GRC Advisor to join the team and work on Key accounts to drive adoption and retention and identify areas for expansion within our platform. This position will leverage our GTM, and value drivers established through combining people, process, and technology. If you are anything like the talented GRC Advisors at Diligent then this feeling you have, might be the desire to serve others- but you are blinded by the limits placed on you in your current role. The Client Success Advisor role is key to Diligent’s Customer Success retention strategy. Key Responsibilities Provide guidance and best practices on configuring, customizing, and optimizing the functionality of the GRC platform and modules to align with clients’ business processes and objectives. Conduct in-depth assessments of clients’ GRC requirements, objectives, and challenges to recommend tailored solutions to address their business needs and goals. Collaborate with clients on internal roadmaps, governance, risk, and compliance requirements to be implemented within Diligent’s platform. Ensure proper understanding and adoption of the platform solutions to identify at-risk clients and help increase usage of the software and modules. Partner closely with internal Product, Customer Success, Support, and Sales teams to drive continuous improvement of the platform based on client use cases. Monitor industry trends, regulatory developments, and emerging best practices in the GRC landscape to proactively share insights and recommendations with clients from a subject matter expert perspective. Required Experience/Skills Minimum of 5-7 years of experience in a client-facing role within the legal, compliance, and entity management or subsidiary governance industry. Adaptive mindset and ability to drive out a meaningful path to how our customers see tangible business value. Ability to build relationships both internally and externally to understand the underpinni

Position Overview Diligent is looking for an experienced GRC Advisor to join the team and work on Key accounts to drive adoption and retention and identify areas for expansion within our platform. This position will leverage our GTM, and value drivers established through combining people, process, and technology. If you are anything like the talented GRC Advisors at Diligent then this feeling you have, might be the desire to serve others- but you are blinded by the limits placed on you in your current role. The Client Success Advisor role is key to Diligent’s Customer Success retention strategy. Key Responsibilities Provide guidance and best practices on configuring, customizing, and optimizing the functionality of the GRC platform and modules to align with clients’ business processes and objectives. Conduct in-depth assessments of clients’ GRC requirements, objectives, and challenges to recommend tailored solutions to address their business needs and goals. Collaborate with clients on internal roadmaps, governance, risk, and compliance requirements to be implemented within Diligent’s platform. Ensure proper understanding and adoption of the platform solutions to identify at-risk clients and help increase usage of the software and modules. Partner closely with internal Product, Customer Success, Support, and Sales teams to drive continuous improvement of the platform based on client use cases. Monitor industry trends, regulatory developments, and emerging best practices in the GRC landscape to proactively share insights and recommendations with clients from a subject matter expert perspective. Required Experience/Skills Minimum of 5-7 years of experience in a client-facing role within the legal, audit, risk, or compliance industry. Adaptive mindset and ability to drive out a meaningful path to how our customers see tangible business

Role Overview Help organizations turn governance, risk, and compliance (GRC) goals into measurable business value. As a Client Success Advisor, you’ll guide key clients in configuring, adopting, and optimizing a GRC platform—strengthening retention, uncovering expansion opportunities, and helping teams work more effectively. You’ll combine GRC expertise, advisory skills, and a strong understanding of client needs to shape practical solutions, improve platform usage, and build lasting partnerships. Your work will influence client outcomes while contributing valuable insights to internal product and go-to-market teams. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Advise clients on configuring, customizing, and optimizing GRC platform functionality to support their business processes and objectives. Assess client requirements, challenges, and goals, then recommend tailored solutions that deliver measurable value. Partner with clients on governance, risk, and compliance roadmaps, translating priorities into effective platform implementations. Drive adoption across the platform and its modules, identifying engagement risks and helping clients increase usage. Help clients identify and implement practical analytics use cases that improve automation, exception management, and reporting. Collaborate with Product, Customer Success, Support, and Sales teams to improve solutions based on real-world client needs. Monitor regulatory developments, industry trends, and emerging GRC best practices to provide proactive, trusted advice. These are the essentials you’ll need to get an interview 5–7 years of experience in a client-facing role within audit, risk, compliance, or a related GRC environment. Strong knowledge of GRC concepts, regulations, industry standards, and software platforms. Experience translating audit, risk, compliance, or business questi

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

Graphcore Director-Post Silicon Validation (Functional) 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. 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. We are opening a new AI Engineering Campus in Austin, Texas which will play a central role in Graphcore's work building the future of AI computing. We are developing the next generation of AI compute, a large-scale system-on-chip (SoC) designed to power future high-performance AI systems. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and validation. You will lead a team delivering post-silicon validation across the full AI SoC, working across silicon, firmware, and platform levels. The role requires a deep technical understanding, strong hands-on debug experience, and the ability to collaborate effectively with hardware, software, and systems engineering teams. Working within the Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. Th

Principal Embedded SW/FW Engineer (Bringup) - Austin, Tx, USA Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential: Understanding of ML

Principal Embedded SW/FW Engineer (Bringup) - Bengaluru, multiple vacancies Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential:

Staff Embedded SW/FW Engineer (Bringup) 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. 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. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team developing C code used to validate cutting-edge, high-performance AI chips and platforms. You will play a critical role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Bringup team, you will be involved with bringing first silicon to life, developing code primarily in C to configure and exercise systems and sub-systems on new silicon devices, and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to, and be responsible for, leading, mentoring, and providing technical guidance to other engineering team members. In this role, you can leverage your experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Respons

#Team Nextdoor Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on. Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 350,000 neighborhoods across 11 countries. Meet your Future Neighbors As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll: Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked Interpret data and report conclusions drawn from their analyses Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights Build data pipelines to create and transform data for analysis of different product features Clean and summarize data to make it accessible for reporting and for data science Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline What You’ll Bring to The House Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field. Three (3) years of years of experience in the role or in a related position. Full term of experience m

Location - Hybrid This is a hybrid role based out of our San Francisco, Corporate Headquarter office, 3 days in the office, 2 days remote OR one of our Hub locations, Boston, MA or Raleigh, NC, which means you may be expected to work from a designated co-working space from time to time, and will otherwise work remotely from home, until such time as a dedicated office is established. About Us Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at http://saucelabs.com . Release Assurance at the Speed of AI | Meet the new Sauce Labs The Role The Senior Director, Growth is an AI-first revenue leader responsible for setting the macro strategy, revenue architecture, and cross-functional alignment of an intelligent, end-to-end pipeline engine. Reporting to executive leadership, this role bridges marketing and sales executive strategy—focusing on expanding our outbound/inbound SDR function, driving predictive pipeline models, and enabling functional marketing leads to scale their teams. Rather than managing day-to-day tactical execution, you will focus on high-level channel architecture, budget optimization, sales leadership alignment, and scaling our revenue operations to maximize global pipeline output. Responsibilities Pipeline Strategy & Executive Revenue Alignment Align on global pipeline target setting, forecasting models, and macro growth strategy across inbound and outbound channels. Champion an agentic AI revenue stack, equipping functional leaders and teams with predictive tools, d