Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid , based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Bring up, run, and debug modern ML models (e.g., transformers) using PyTorch or TensorFlow. Analyze model behavior and performance, and identify bottlenecks across the stack. Improve efficiency, correctness, and scalability of model execution in real systems. Work closely with compiler, kernel, and hardware teams to drive performance and system-level improvements. Help translate state-of-the-art model architectures into production-grade, high-performance deployments. What We Need Strong experience building and working with ML models in PyTorch or TensorFlow. Strong understanding of mod
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The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in
Job Details: Job Description: As a Facilities Mechanical Engineer, you will play a pivotal role in ensuring the reliable operation and maintenance of Intel's advanced mechanical systems, supporting our cutting-edge manufacturing, cleanroom, and research and development activities. Your work will directly impact Intel's ability to innovate and deliver world-class technologies by maintaining the critical infrastructure that enables peak operational performance. This role offers a unique opportunity to drive engineering excellence, collaborate with cross-functional stakeholders, and shape the future of Intel's facilities globally. Key Responsibilities: Ensure the availability, reliability, and maintenance of mechanical systems such as oil-free air systems, HVAC systems, chilled water plants, boilers, environmental abatement systems, and compliance exhaust systems. Support daily tactical efforts to meet safety, reliability, and environmental targets for mechanical systems. Design and analyze mechanical systems and equipment, troubleshoot systematic issues, and provide evaluations, recommendations, and solutions to resolve problems. Develop engineering scopes of work for mechanical projects and conduct design reviews to ensure system integrity and performance. Conduct feasibility studies and testing on new and modified designs, while overseeing prototype fabrication and design testing. Partner with internal business units and operations teams to deliver engineering solutions tailored to their specific needs.
Leidos is seeking a Test and Integration Engineer to lead cutting-edge testing and validation efforts within the Undersea Systems Division (USD) . This role is a unique opportunity to drive innovation in testing underwater vehicle systems, maritime sensors, subsea telemetry, and ISR solutions that support critical defense and national security missions. You'll contribute to a multidisciplinary team focused on testing, integrating, and validating advanced maritime technologies, ensuring system reliability and performance from prototype design to full-scale system deployment for ongoing Navy missions. Leidos’ Undersea Systems Division is a recognized leader in C4ISR technologies, delivering innovative, mission-critical solutions across sensor networks, unmanned systems, and tactical platforms . We’re known for achieving “industry firsts” in the most challenging maritime domains. Join us and be part of a world-class team delivering unmatched solutions for today's most pressing maritime missions. Why Join Us? Make an Impact : Your work will directly support U.S. maritime dominance and national security. Lead Innovation : Be at the forefront of applying innovative technology and autonomy to real-world maritime systems. Work with Experts : Collaborate with a top-tier team of engineers, scientists, and technicians located across the U.S. Shape the Future : Influence both the strategic and tactical direction of next-generation subsea technologies. What You’ll Do Test and Validate: Write, develop and execute comprehensive test plans, procedures, and protocols to ensure system functionality, reliability, and compliance with requirements. Integrate systems and conduct hands-on testing: Write, develop, and execute integration plans to bring complex systems together. Perform field</b
Opportunity Overview: We are seeking a Lead Software Engineer to join our Integrations team. In this role, you will be designing, developing, and scaling highly available healthcare integration systems supporting prior authorization workflows across providers, payers, and delegated entities. You'll direct a fast-paced, autonomous,agile team of software engineers in the design, development, and operational support of a growing enterprise integration platform. This is an opportunity to drive technical excellence at the intersection of healthcare interoperability and modern distributed systems. What you’ll do: Technical Leadership: Provide technical leadership across architecture, system design, platform scalability, reliability, and operational excellence. Platform Engineering: Design and build scalable, resilient, and high-performing systems that support critical business workflows and enterprise integrations. Integration Solutions: Lead the development and maintenance of secure integrations with internal and external platforms, partners, and third-party systems. Cloud & Automation: Drive cloud infrastructure, deployment automation, and software delivery practices that enable reliable and efficient releases. Distributed Systems: Design and support event-driven and distributed architectures that enable scalable and fault-tolerant processing. Operational Excellence: Establish monitoring, observability, and incident response practices to ensure system reliability, performance, and availability. Quality Engineering: Champion automated testing, quality assurance, and engineering best practices throughout the software development lifecycle. Production Support: Lead the resolution of complex production issues and drive continuous improvement in platform stability and operational efficiency. Cross-Functional Collaboration: Partner with product, operations, data, security, and business stakeholders to deliver solutions aligned with organizational goals. Agile Delive
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Join our Site Reliability Engineering team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Site Reliability Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking SREs who are passionate about building and maintaining resilient systems at scale. Your mission will be to design and implement robust monitoring solutions, automate operational tasks, and continuously improve our infrastructure's reliability and performance. You will: Design and Implement Observability Solutions : Develop comprehensive monitoring and alerting systems using modern observability tools. Create dashboards and metrics that provide real-time visibility into system health and performance. Implement logging strategies that enable quick problem identification and resolution. Drive Automation and Infrastructure as Code : Architect and implement infrastructure automation solutions using tools like Terraform, Ansible, or Pulumi. Design and maintain CI/CD pipelines that enable reliable and consistent deployments. Create self-healing systems that can automatically respond to common failure scenarios. Establish SLOs and SLIs : Work with product and engineering teams to define and implement Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Build systems to track and report on these metrics, ensuring we maintain high reliability standards while balancing innovation speed. Incident Management and Response : Lead incident response efforts, conducting thorough post-morte
NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E
JOB TITLE Site Reliability Engineer A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. WHAT YOU’LL DO You will play a highly critical operational role where you will apply a combination of software and systems engineering skills to develop and maintain a complex set of distributed, real-time systems that serve critical stakeholders in Point72’s Global Macro business. You will focus on optimizing the operations of existing systems and infrastructure in an efficient manner, through a strict adherence to automation and tooling Specifically, you will: Build out foundational technical components of an extensive SRE program across multiple complex systems, both new and existing • Collaborate with our development and quant teams to ensure that ongoing change is consistent with a pre-determined, measurable set of SLOs spanning multiple complex user interactions with our systems • Monitor system capacity and performance, identifying and addressing potential future bottlenecks and sources of instability before they become impactful to our stakeholders • Review and provide feedback on automation code developed by peers to maintain high standards of code quality and efficiency • Troubleshoot and resolve system issues, analyzing their impact on infrastructure and service operations • Participate in or lead design reviews with peers and stakeholders, evaluating and selecting the best technologies and automation strategies for our needs WHAT’S REQUIRED We are looking for highly motivated, proactive engineers
Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. Contribute
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. C
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Join our Site Reliability Engineering (SRE) team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Staff Site Reliability Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking Staff SREs who are passionate about building and maintaining resilient systems at scale. Your mission will be to proactively find and analyze reliability problems across our stack, then design and implement software and systems to create step-function improvements. You will design robust observability solutions, lead incident response, automate operational tasks, and continuously improve our infrastructure's reliability, all while mentoring and educating the broader engineering team to make reliability a core value at Replit. You Will: Architect and Implement Observability: Design, build, and lead the implementation of comprehensive monitoring, logging, and tracing solutions. Create dashboards and metrics that provide real-time visibility into system health and performance, enabling proactive issue detection. Define and Drive Reliability Standards: Work with product and engineering teams to define, implement, and track Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Build systems to monitor and report on these metrics, holding teams accountable and ensuring we maintain high reliability standards while balancing innovation speed. Lead Incident Management and Response: Act as a senior leader during high-impact incidents, guiding the team to rapid resolution
We anticipate the application window for this opening will close on - 30 Sep 2026 Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life The Acute Care & Monitoring (ACM) business develops technologies that help clinicians monitor, assess, and manage patients across the continuum of care. Within ACM, the Test Engineering function supports product development, verification, reliability, and manufacturing readiness through the design and execution of test methods, fixtures, and equipment used to evaluate product performance and system functionality. This team partners closely with systems, mechanical, electrical, software, quality, and manufacturing engineering teams to support the development and sustainment of medical technologies. This position is based in Lafayette, Colorado and is an onsite role. Travel up to 10% may be required to support testing activities, cross-functional collaboration, and business needs. As a Mechanical R&D Engineer II, you will support system-level, reliability, mechanical, and electrical testing activities for Acute Care & Monitoring products. This role combines hands-on laboratory testing, fixture development, data analysis, and cross-functional collaboration to evaluate product performance, investigate issues, and support verification activities throughout the product lifecycle. Primary Responsibilities <li
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Software Engineer at on the Training Infrastructure team, you'll architect and lead development of our training platform, supporting top tier research engineers and model developers. You'll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor their workloads with high performance and reliability. You’ll own scheduling, storage, networking, reliability, and observability of technical systems in the training stack EXAMPLE INITIATIVES Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done RESPONSIBILITIES Design and architect scalable infrastructure systems for our ML training platform (e.g. scheduling, storage, and networking) Partner closely with developers and research engineers to translate complex training requirements into technical solutions Design and architect a global training scheduler Design and architect reinforcement learning systems and continuous learning pipelines Drive long-term improvements to improve reliability of systems and velocity of development Partner closely with SRE and Capacity teams to unlock state of the art training infrastructure Make critical architectural decisions balancing performance with system reliability Lead technical discussions and mentor junior engineers on infrastructure best practices Contribute to long-term technical strateg
About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve people's lives. About the Role We are seeking a lead thermal simulation engineer to help accelerate the design and development of next-generation robotic systems through modeling, simulation, and analysis. You will work closely with mechanical, electrical, controls, and robotics engineers to evaluate designs before hardware is built, identify risks early, and guide critical architecture decisions. This role spans structural and thermal analysis and design across robotic subsystems including actuators, mechanisms, structures, electronics, and integrated systems. You will develop simulation workflows that improve engineering velocity, increase confidence in design decisions, and help us build more capable, reliable, and manufacturable robotic platforms. This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Perform thermal simulations to assess heat generation, cooling strategies, thermal interfaces, and system-level thermal performance Partner with mechanical, electrical, and controls engineers to influence design decisions early in development Build simulation models to evaluate robotic actuators, transmissions, mechanisms, structures, soft goods, and integrated assemblies Correlate simulation results with physical testing and develop methodologies to improve model accuracy Support architecture trade studies by evaluating design concepts before hardware is built Develop simulation workflows, standards, and best practices that scale across the robotics o
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