Functional Safety Engineer, Energy Storage

Redwood Materials is pioneering a sustainable circular economy for lithium-ion batteries by transforming recycled materials into critical inputs for energy storage and next-generation battery technologies. We are seeking a motivated and experienced Functional Safety Engineer to join our team and play a key role in ensuring compliance with functional safety standards and advancing the safe deployment of new energy storage system (ESS) technologies. 

Responsibilities will include: 

• Functional Safety & Compliance: Lead compliance activities for ESS functional safety with a focus on UL 1998 (Software in Programmable Components), UL 991 (Tests for Safety-Related Controls Employing Solid-State Devices), and UL 5500 (Remote Software Updates). Support certification efforts and align product development with functional safety requirements
• Standards Application & Development: Apply safety principles and methodologies to ESS hardware and software. Facilitate and lead the development of FMEA’s, hazard analyses, safety cases, and test strategies. Represent Redwood in standards development activities to help shape emerging requirements for ESS functional safety
• Certification Management: Work with certification bodies (NRTLs) to establish and manage compliance programs for new technologies, ensuring timely approvals to support product introduction milestones. Partner closely with engineering and product teams to integrate safety requirements into development cycles
• Team Support & Alignment: Translate complex safety standards into actionable requirements for cross-functional teams. Provide technical guidance on functional safety practices and address feedback to align product designs with compliance needs
• Risk Management: Develop, document, and execute hazard mitigation and validation strategies. Support testing and verification activities to ensure system safety performance. Coordinate with internal and external stakeholders to resolve compliance and safety issues proactively
• Stakeholder Collaboration: Collaborate with engineering, manufacturing, and product design teams to streamline compliance and safety processes for ESS. Maintain strong relationships with certification bodies and industry partners to stay ahead of evolving safety requirements

Desired Qualifications: 

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Systems Engineering, or related field 
• Hands-on experience in embedded software development, ideally within safety-critical or regulated environments
• Preferred experience developing or working directly with microcontroller-based systems, including low-level software or firmware
• Proficiency in C for real-time embedded systems
• Strong background in UL 1998, UL 991, and UL 5500
• Familiarity with international functional safety standards such as IEC 61508, IEC/UL 60730, ISO 26262, or ISO 13849 (preferred)
• Experience working with Energy Storage Systems, power electronics, or safety-critical systems
• Demonstrated ability to apply functional safety methodologies (e.g., hazard analysis, safety cases, V&V planning)
• Experience managing compliance or certification processes with third-party testing/certification bodies
• Strong organizational skills, with high attention to detail
• Excellent communication skills, with the ability to explain complex technical requirements to diverse stakeholders
• A passion for sustainability and making the world a better place!

Software Validation Engineer, Energy Storage 

The Redwood Vision: Architecting the Future of the Grid 

We are at the precipice of a global energy transition. At Redwood Materials, we are moving beyond battery recycling to build the most advanced, circular energy ecosystem on the planet. Our goal is to shift the industry from static, hardware-heavy infrastructure toward agile, software-defined energy assets. The Software Validation team ensures that these complex systems are safe, resilient, and ready for grid-scale deployment. 

As a Software Validation Engineer, you are the bridge between pure code and physical reality. You will design and maintain the environments—Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL)—that allow us to stress-test our power electronics and site controllers. Your mission is to build the automated frameworks that catch edge cases before they hit the field, ensuring every product we ship meets the highest standards of reliability. 

Key Responsibilities 

• Validation Environment Design: Architect and scale our SIL and HIL environments (using platforms like Typhoon HIL, Opal-RT, or similar) to provide high-fidelity simulations of battery assets and grid conditions
• Test Automation Frameworks: Lead the development of automated test suites in Python. You will transition our validation processes from manual intervention to a fully automated, scalable framework
• V&V Strategy: Define and execute comprehensive Verification and Validation (V&V) plans, ensuring all software requirements for the site controller and embedded power electronics are met under normal and fault conditions
• CI/CD Integration: Integrate automated HIL/SIL testing into our CI/CD pipelines, providing real-time feedback to the development teams and serving as the final gate for production-ready code
• Hardware-in-the-Loop Interfacing: Design custom interface hardware and wiring for HIL benches, bridging physical I/O from our controllers to simulated power stages
• Root Cause Analysis: Work closely with the firmware and systems teams to debug complex failures found during validation, using logic analyzers, oscilloscopes, and telemetry logs to pinpoint issues

Qualifications 

• Background: A BS or MS in Electrical Engineering, Computer Engineering, or a related field, combined with 2+ years of professional experience in software validation or test automation for hardware-focused systems
• HIL/SIL Mastery: Proven experience with real-time simulation platforms (Typhoon HIL, Opal-RT, or dSPACE) and a deep understanding of how to model power electronics components in a virtual environment
• Automation Toolchain: Expert proficiency in Python (specifically for test automation frameworks like Pytest) and familiarity with Rust and C/C++ to navigate embedded codebases
• Hardware Literacy: Comfortable in a high-voltage lab environment. You should be proficient with standard lab equipment (oscilloscopes, power supplies, electronic loads) and digital protocols like CAN, SPI, and Ethernet
• Systematic Thinking: A dedicated mindset for "breaking" software. You have a track record of finding critical edge cases in complex state machines and control loops
• Infrastructure: Experience with Git, Jenkins/GitHub Actions, and containerization tools like Docker for managing consistent test environments

Infrastructure Software Engineer, Energy Storage 

The Infrastructure Engineer is responsible for designing, building, and maintaining the foundational platform infrastructure that enables our engineering team to develop and deploy Battery Energy Storage Systems reliably and at scale. This role serves as a force-multiplier across the organization, owning edge fleet management, server provisioning, and deployment automation while ensuring systems are secure, scalable, and performant. The position partners closely with cross-functional engineering teams to translate early deployment learnings into platform improvements and drive resolution of scalability, reliability, and security challenges. Success in this role requires deep technical expertise, a collaborative mindset, and the ability to thrive in an ambiguous, fast-paced, early-stage environment. 

Responsibilities will include: 

• Design and own the rollout of edge Kubernetes fleet management, automated server provisioning, and software update pipelines to support scalable and reliable system deployment. 
• Evaluate server hardware and operating systems to help define the architecture of the organization's next-generation energy storage platform. 
• Identify and resolve hard infrastructure problems, including scalability bottlenecks, reliability gaps, performance issues, and security vulnerabilities. 
• Build and maintain tooling and services used to validate software systems at scale, including performance and reliability testing frameworks. 
• Serve as a technical resource for the broader engineering team through pair programming, in-office working sessions, and hands-on project leadership. 
• Translate learnings from early deployments and customer pilots into concrete, measurable improvements to platform infrastructure. 
• Reinforce a team culture grounded in engineering excellence, curiosity, inclusivity, and a willingness to take action and learn from mistakes. 

Desired Qualifications: 

• 5+ years of relevant industry experience in infrastructure, platform, or site reliability engineering. 
• Strong grasp of system design principles and real-world experience building available, reliable, scalable, and secure distributed systems. 
• Experience designing, implementing, and maintaining secure network systems and infrastructure. 
• Genuine interest in server hardware fundamentals and how software and hardware interact at the platform level. 
• Ability to work comfortably with ambiguity, prototype solutions iteratively, and learn rapidly from early-stage work. 
• Strong written and verbal communication skills, with the ability to explain complex systems clearly to both technical and non-technical audiences. 
• Ability to manage multiple workstreams, shifting priorities, and competing deadlines in a fast-paced, early-stage environment. 

Software Simulation Engineer

We are looking for a Software Simulation Engineer to design and build the core architecture of our simulation platform. You will be responsible for the infrastructure that validates our intelligent systems before real-world deployment. Your focus will be on creating a scalable, high-performance virtual environment that seamlessly integrates flight software, autonomy stacks, and external models.

Role

• Simulation Architecture: Design, build, and maintain the core infrastructure, data pipelines, and timing mechanisms for our system-level and Software-in-the-Loop (SIL) simulation environments.
• Framework Development: Build robust APIs and interfaces that allow cross-functional teams to easily plug their specific sensor, actuator, and physics models into the broader simulation.
• Software Integration: Integrate flight software, autonomy stacks, and control algorithms directly into the simulator.
• Testing Infrastructure: Develop the backend tooling and automated test frameworks needed to run large-scale simulations, verify system behavior, and catch edge cases.
• Cross-Functional Sync: Act as the simulation platform owner, partnering with hardware and controls teams to ensure the architecture supports their testing requirements and scales effectively.

Requirements 

• BS or MS in Computer Science, Software Engineering, Systems Engineering, or a related field.
• 3+ years of experience in software simulation, systems architecture, or complex software development.
• Expert in Python with strong working knowledge of C++.
• Hands-on experience architecting, extending, or maintaining custom software simulators, test harnesses, or large-scale software frameworks.
• Solid understanding of system-level networking and data routing (e.g., Ethernet, UDP/TCP, CAN).

Bonus

• Background in aerospace, automotive, or robotics.
• Familiarity with Embedded Linux, RTOS, or supporting downstream Hardware-in-the-Loop (HIL) setups.
• Experience with CI/CD pipelines and scaling simulations in cloud environments.

About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $130,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $130,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

You’ll join the Data Platform team, responsible for building the backend services and “data products” that power how data moves through the company. We create the core platform primitives — high-quality event streams, reliable access layers, and developer-friendly APIs/tools — so teams across the org can self-serve what they need and ship faster. You’ll contribute to backend services that create value from our company data, and help make our data platform more self-serve so product and engineering teams can easily create and operate event-driven architectures, publish/consume streams, define access models, and ship data products end-to-end. You’ll also work on LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products — with mentorship and support from experienced engineers.

Responsibilities

• Contribute to backend services that enhance the data platform’s capabilities (APIs, control planes, automation, governance).
• Help enable DIY workflows for teams across the company:

• • Define/publish events and schemas
  • Create/consume streams and subscriptions
  • Establish access models (authz, row/field-level controls where applicable)
  • Manage dataset/catalog metadata, lineage, versioning, and retention

• Contribute to end-to-end data products: ingestion → validation/quality → enrichment → serving (APIs/streams) → observability → adoption.
• Work on prompt categorization and enrichment services: taxonomy design, labeling workflows, classifier/rules integration, evaluation, drift/quality monitoring, and safe rollouts.
• Learn to own reliability: SLOs, alerting, performance/cost tuning, incident response, and postmortems.
• Partner cross-functionally with ML/LLM, infra, security, and product teams to define crisp contracts and deliver durable platform primitives.

Requirements

• 0–4 years building production or project-based backend systems (internships, coursework, and personal projects count).
• Solid fundamentals in at least one backend language (e.g., Go, Python, Java, Rust) and some exposure to API design (REST).
• Eagerness to own work end-to-end: design docs, implementation, testing, deployment, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, and a desire to build systems that are easy to evolve.
• Basic data modeling and SQL skills, and some familiarity with at least one of:

• • Streaming/eventing (Kafka/PubSub/Kinesis, etc.)
  • Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
  • OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)

• AI augmentation curiosity:

• • You’re curious about how engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, retrieval/knowledge grounding), and you’re eager to apply this to your own work.
  • You understand that AI tools can fail or create issues, and you’re thoughtful about when and how to apply them.

Nice to have

• Any exposure to self-serve platforms, developer tooling, or multi-tenant services.
• Coursework or projects involving LLM/AI products: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Passion for good quality code, highly readable, SOLID principles, design patterns, Domain Driven Design.
• Awareness of security and governance basics: least-privilege access, auditability, data retention, PII handling.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $120,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe Terminal helps our users extend their online presence to the physical world. The Terminal team’s mission is to make it as easy for businesses to accept in-person payments as the Stripe API has done for online payments. Stripe was founded to make it easier for developers to accept payments. We’ve solved a small part of that problem, but our ambition is to go much further. 

Android engineers on the Terminal team will build and enhance the Device Platform including the applications and services that run on the physical Terminal devices.  This also includes building the frameworks for other engineers, both internal and external to stripe, to develop on our custom platform with ease.

What you’ll do

Responsibilities

• Design, build and maintain Android apps and SDKs in Kotlin
• Develop Android payment applications for a variety of devices and form factors
• Work with engineers, product managers, designers, and stakeholders across the company to bring new features and products to Stripe’s mobile users
• Collaborate with Android developers who work on the Stripe mobile apps and Stripe Terminal to set best practices for Android development across the company
• Work with user research and product design to understand users and address their needs

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Have a strong technical background, with 2-6 years of experience in Android development. 
• Listen well and internalize the best ideas from all over the organization 
• Prefer simple solutions and designs over complex ones, and have a good intuition for what is lasting and scalable
• Thrive in a collaborative environment involving different stakeholders and subject matter experts
• Can put yourself in the shoes of your users and be a steward of crafting great developer and consumer experiences

Preferred qualifications

• Custom hardware experience on Android platform
• Payments expertise or knowledge
• Backend Infrastructure or services experience
• Based in the PST time zone

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe Terminal helps our users extend their online presence to the physical world. The Terminal team’s mission is to make it as easy for businesses to accept in-person payments as the Stripe API has done for online payments – building for Unified Commerce. With Terminal, businesses can unify their in-person and online experiences, unlocking payments use cases that are right for their business model – whether it’s creating a modern retail experience, extending their website to a pop-up store, or enabling a mobile point-of-sale at their next event.

Within Terminal, the Developer Productivity team empowers mobile, full-stack and embedded/firmware engineers to ship high-quality products quickly and safely. We build tools, processes and infrastructure that accelerate engineers across multiple teams. Our work is critical to supporting Stripe’s in-person payment products and, ultimately, to helping increase the GDP of the internet.

We own a diverse tech stack, including build and developer productivity tooling for mobile engineers; release tooling that enables Terminal releases across SDKs, Android apps and firmware; and test automation infrastructure that helps product engineers ensure the quality and reliability of what they ship. As an engineer on this team, you’ll shape and deliver major pieces of this tooling and infrastructure and help raise the bar for developer experience across Terminal.

What you’ll do

Responsibilities

• Design, build and maintain tools, libraries and infrastructure that improve the productivity of Terminal engineers across mobile, backend and embedded systems.
• Collaborate closely with mobile engineers to understand their workflows and pain points and translate them into practical short-term and long-term solutions.
• Contribute to and improve our build, CI/CD and test automation systems for Terminal SDKs, Android apps and firmware.
• Work with stakeholders across Terminal to prioritize work, balance competing needs and ensure your solutions integrate cleanly into existing workflows.
• Own projects end-to-end, from problem discovery and design through implementation, rollout and ongoing operation.
• Participate in code reviews, design discussions and documentation to maintain a high bar for code quality, reliability and developer experience.
• Mentor other engineers in areas such as build, test and release best practices, helping to spread strong developer productivity practices across the team.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• BS or MS in Computer Science or a related field, or equivalent practical experience.
• 6+ years of software engineering experience, including meaningful experience with backend systems and at least one of: Android/mobile or embedded/firmware development.
• Experience designing, implementing and maintaining production systems or developer tooling.
• Understanding of how to build scalable, reliable and observable services, pipelines, or tooling.
• Experience owning projects from design through implementation, rollout and ongoing support.
• Ability to thrive in a collaborative environment involving multiple stakeholders and subject matter experts.
• Strong communication skills and the ability to explain technical concepts clearly to different audiences.
• Based in the PST time zone

Preferred qualifications

• Proficiency in one or more of: Kotlin, Java, or Go.
• Experience building tools or platforms to improve developer productivity, with clear empathy for internal developer users.
• Experience with CI/CD tooling and pipelines (e.g. Jenkins, GitLab CI, GitHub Actions) and modern build systems.
• Experience designing and maintaining automated testing infrastructure (e.g. integration/end-to-end tests, test orchestration, or reducing test flakiness).
• Experience with Android build and test tooling (e.g. Gradle, emulators, device farms) or firmware build pipelines.
• Experience in payments, point-of-sale, or hardware-integrated systems is a plus.

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe Terminal helps our users extend their online presence to the physical world. The Terminal team’s mission is to make it as easy for businesses to accept in-person payments as the Stripe API has done for online payments. With Terminal, businesses can unlock in-person payments use cases that are right for their business model—whether it’s creating a superb retail experience, extending their website to a pop-up store, or enabling a mobile point-of-sale at their next event. 

We’re looking for an experienced product manager to lead and shape the future of the software platform that powers Stripe Terminal’s devices portfolio. Working closely with your engineering partners you will design, build and launch device software capabilities that delight users and differentiate Stripe’s solutions in the market. Working closely with our hardware experts you will build the multi-year strategy for how Stripe will continue to enhance the scalability, reliability, usability, and market differentiation of the software capabilities of our in-person commerce devices. 

In this role, you will work with a spectrum of users, from our largest platforms to small start ups as well as external technology partners to deeply understand user needs and market trends. You will obsess over stability, scalability, and expanding our product while delivering the best in person experiences in the world. 

What you'll do:

Set a motivating multi-year vision for device software in partnership with the Hardware team and then break it down into measurable, meaningful milestones for the Terminal OS Platform Team and the Firmware team. This includes creating buy-in, crafting roadmaps and OKRs, and navigating trade-offs.

• Partner with software and hardware engineers to deeply understand the technology that our devices rely on and how to build on that technology to support exponential growth and a world-class user experience. These experiences will include (but are not limited to) device boot up, device software updates (including AOSP, firmware and applications), device security, software and device performance, connectivity and devices accessories.
• Partner with cross-functional partners to research, document, and deeply understand what Terminal customers need to enable an excellent in person payments experience. 
• Build empathy with our end users and the differentiation they aim to deliver for their merchants.
• Deeply research and understand the competitive landscape and translate that understanding into differentiating features for your product suite.
• Collaborate with the Partnerships team to develop a compelling roadmap for how we can extend Terminal growth via third-party hardware partnerships and clearly communicate the business value of these partnerships in the context of our wider Terminal Hardware roadmap to gain alignment across Terminal and Stripe leadership.
• Use metrics to inform your point of view and leverage analytics to measure success.
• Define product requirements, provide clear guidance on prioritization, and support decisions related to development sequencing. You will also participate in sprint planning rituals to deliver against those requirements and the overall roadmap.
• Leverage your technical knowledge and experience to help your team make technical trade off decisions. 

We’re looking for someone who has:

• 8+ years of product management experience or equivalent
• Demonstrated success and strong execution track record in building and sustaining scalable technology products.
• Great interpersonal skills and strong verbal and written communication. You can collaborate and thrive in productive, healthy debate done with mutual respect and shared goals. You can make complex concepts accessible with clear communication
• Proven track record of successful stakeholder management including executive communications, handling escalations, and advocating for ongoing investment in your product.
• Experience working on products with developer interfaces (App deployment, APIs, SDKs); hardware or hardware-related product experience a plus.
• Technically adept systems thinker, ideally with a Computer Science or equivalent degree or experience working as a software engineer
• Open to travel to Asia, including traveling at times to our Hong Kong or Taiwan locations.

Experience in 1 - 2 of the following areas are nice to have:

• Mobile device management
• Android operating system internals
• Hardware build and lifecycle management
• Payments and/or eCommerce
• Experience successfully building and launching 0-1 products 

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

We are seeking a visionary and technically strong Staff Materials Engineer to lead the development and advancement of material technologies that are core to the Oura product experience. This role will focus on driving innovation and execution across metal surface treatments, PVD/CVD, platings and other novel inorganic coating materials - ensuring performance, reliability, and premium user experience across current and future hardware platforms.

What You’ll Do:

• Manage a roadmap for materials engineering across metal surface treatments, PVD/CVD, platings and emerging technologies.
• Drive R&D and materials selection efforts for current and next-generation products, balancing form factor, performance, biocompatibility, manufacturability, and sustainability.
• Establish and optimize material and bonding processes for high-volume manufacturing.
• Partner with PD, ID, and Ops teams to understand needs and integrate materials solutions early in the product development lifecycle.
• Define standardized materials testing and coupons to characterize new and existing materials within the area of expertise.
• Work with external vendors and strategic partners to evaluate new materials and coatings, qualify processes, and ensure scalability and reliability.
• Define and oversee materials validation, characterization, and reliability testing methodologies.
• Collaborate closely with Reliability and Regulatory teams to ensure material compliance and performance in real-world use conditions.
• Identify and mitigate material risks across the product lifecycle, from prototype to production and field usage.

What We’re Looking For:

• Bachelor's degree in Materials Science, Chemical Engineering, Mechanical Engineering, or a related field. 
• 10+ years of experience in materials engineering of PVD/CVD and metal surface treatments
• Proven experience developing materials and processes for consumer electronics, medical devices, or wearables.
• Strong background in materials characterization, surface chemistry, and process development.
• Strong global connections and experience working with contract manufacturers and materials suppliers across Asia and globally.
  
  

Nice to Have:

• Advanced degree (MS/PhD) in Materials Science, Chemical Engineering, Mechanical Engineering, or a related field.
• Experience with biocompatibility and regulatory requirements for skin-contact products.
• Background in sustainability-focused material development.

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1: $198,050 - $267,950

Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.

We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Disclaimer: Beware of fake job offers!
We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:

• Our jobs are listed only on the ŌURA Careers page and trusted job boards.
• We will never ask for personal information like ID or payment for equipment upfront.
• Official offers are sent through Docusign after a verbal offer, not via text or email.

Stay cautious and protect your personal details.

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What you’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a remote role

JR: 2026-7748

#LI-Remote

We want people who are passionate about troubleshooting complex problems with systems, networking and storage at scale.

We are looking for a seasoned system administrator to help us keep the cloud running smoothly. Reporting to the manager of Cloud Operations, the GPU Operations Engineer monitors and provides first-response to all cloud health issues that impact, or could potentially impact, customer experience - internal or external. You will interface with teams across the organization to research and troubleshoot issues from single droplets to cloud-wide disturbances. Our workweek spans five days, and that may involve working on weekends.

What You'll Be Doing: 

• Ensuring maximum uptime for our global infrastructure
• Automating processes and building tools to improve operational efficiency
• Coordinating operational work across teams to improve the platform with minimal impact

What You'll Add to DigitalOcean:

• Solid experience with Linux operating systems or Networking and day to day upkeep
• Familiarity with virtualization technologies and troubleshooting virtual machine instances
• Familiarity with containerization technologies and troubleshooting containers
• Familiarity with IPv4 Networking and troubleshooting (CCNA equivalent)
• Basic storage concepts and technologies
• Experience with monitoring systems and incident management
• Experience scripting in one or more of the following languages: Bash, Python, or Go
• Experience with GPU hardware or AI/ML, and Kubernetes
• A passion for good documentation and open communication
• Proven ability to learn!

Compensation Range: 

• $107,000 - $134,000

*This is a remote role

JR: 2026-7423

#LI-Remote

itD is seeking a Software Quality Assurance Engineer to drive the verification and validation of smart camera products, ensuring high-quality releases through comprehensive manual and automated testing. This role plays a critical part in delivering reliable, user-focused solutions by identifying edge cases, improving product usability, and embedding quality throughout the development lifecycle. The ideal candidate will bring deep experience in software testing, automation, and system validation, along with a proven track record of uncovering defects and enhancing product performance.

Location: Hybrid – San Francisco, CA (candidates must be able to visit the office multiple times per week if requested)
Pay Range: $26 - $27 hourly
Duration: 2 months

We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.

Responsibilities:
• Analyze and validate product requirements and technical solutions to ensure test coverage and quality outcomes.
• Design and execute detailed manual test plans to identify edge cases, usability issues, and integration gaps.
• Identify, log, reproduce, and verify defects, partnering closely with engineering teams for root cause analysis.
• Develop and maintain automated test scripts using scripting languages such as Python or Ruby.
• Document test cases, procedures, and results to support traceability and knowledge sharing.
• Collaborate cross-functionally to support release validation and ensure product readiness.
• Advocate for the end-user experience by proactively identifying risks and quality improvements.

Internal Responsibilities:
• Attend regular internal practice community meetings.
• Collaborate with your itD practice team on industry thought leadership.
• Complete client case studies and learning material (blogs, media material).
• Build out material to contribute to the Digital Transformation practice.
• Attend internal itD networking events (in person and virtual).
• Work with leadership on career fast-track opportunities.

Required Qualifications and Skills:
• 5+ years of experience in software testing and test automation.
• Strong experience with manual and exploratory testing, including identifying edge cases and integration issues.
• Proficiency in at least one scripting language (e.g., Python, JavaScript, or Ruby).
• Experience developing, maintaining, and executing automated test frameworks.
• Solid understanding of software development lifecycle (SDLC), testing methodologies, and defect lifecycle.
• Working knowledge of Linux environments, including basic networking and CLI tools.
• Ability to work independently, communicate effectively, and meet project timelines.

Preferred Qualifications and Skills:
• Experience testing hardware-integrated or IoT-based products.
• Familiarity with cloud-based systems and distributed applications.
• Exposure to AI-assisted testing tools or modern test automation practices.
• Experience working in agile or cross-functional product teams.

Education:
• Bachelor’s degree in a relevant field or equivalent work experience required.

Location: Austin, TX or San Francisco, CA

Solution Architect, AI / Cloudflare Developer Platform 

As a Solution Architect, Cloudflare AI / Developer Platform and a member of the sales team, you will help customers understand the value proposition of the Cloudflare Developer Platform and demonstrate how to effectively build applications with our products. 

Every day as a Solution Architect is different. You will utilize both technical and business skills to advise customers and sales teams, support strategic opportunities, architect innovative solutions, and develop proofs of concept / demonstrations. Your technical knowledge of Cloudflare’s products and system design will be vital to designing solutions that meet our customers’ needs and expectations.

Serving as a trusted technical advisor, Solution Architects guide and enable clients, partners, and teams within Cloudflare on product capabilities, positioning and competitive intelligence. You will form a tight feedback loop with product, product marketing, and technical pre-sales to refine and evolve our products. 

The ideal candidate possesses a consultative mindset, demonstrable success working with customers, and deep, practical knowledge of modern web technologies, cloud architecture, and experience building on a distributed serverless platform. No matter your background, you have natural curiosity and desire to solve problems, achieve goals, and design the most elegant and efficient solutions to address client needs. A successful Solution Architect at Cloudflare is able to act as a trusted advisor for our customers, while balancing the technical and business needs of the role – actively building and regularly presenting technical solutions to varied audiences.

Responsibilities

• Partner with the sales organization to drive revenue, new customers and pipeline of AI and Developer Platform solutions. 
• Lead technical discovery with customers and jointly architect best practice solutions to meet customer needs.
• Collaborate with cross-functional teams including product management, sales, and marketing to drive developer platform revenue and customer adoption.
• Present to strategic customers as an expert of our Developer Platform solutions.
• Align Director and C-Level perceived business and technical value with Cloudflare developer solutions.
• Provide succinct feedback to cross-functional teams to deliver relevant Developer content, use cases, customer stories, and data driven value propositions.

Skill Requirements

• 5+ years of experience selling or supporting technical sales in the cloud computing industry.
• Deep technical expertise across cloud infrastructure and AI/ML — you have built production systems that combine both as a solutions engineer, entrepreneur, or solution architect.
• In-depth knowledge of at least one major public cloud provider (e.g., AWS, GCP, Azure).
• Practical knowledge and experience designing systems. You have built and deployed a production web application either professionally or as a hobbyist and are able to clearly articulate the design and explain the considerations / trade-offs. You are able to hear a clear, non-technical description of an application, ask clarifying questions, and quickly design a high-level, conceptual architecture.
• Software development experience delivering full-stack applications, preferably using modern JavaScript frameworks, a variety of databases, and Serverless tooling. Experience building with modern coding assistants.
• Strong understanding of developer workflows (branching, versioning, CI/CD practices, system integrations).
• Knowledge of key market players/competitors in the cloud computing, AI and storage spaces.
• Up to 30% travel.

Other desirable skills areas include:

• You’ve built something on Cloudflare Workers.
• AWS Solutions Architect or GCP Cloud Architect certifications.
• Providing structured customer feedback to influence product direction.
• Actively stay up-to-date with industry trends and advancements in cloud computing to inform product strategy and roadmap.

Compensation
Compensation may be adjusted depending on work location. 
This role is eligible to earn incentive compensation under Cloudflare’s Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan.

For Bay Area based hires: Estimated annual salary of 212,000.00 - 292,000.00

Equity
This role is eligible to participate in Cloudflare’s equity plan.

Benefits
Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave

Location: Austin, TX; San Francisco, CA

Solution Architect, AI / Cloudflare Developer Platform 

As a Solution Architect, Cloudflare AI / Developer Platform and a member of the sales team, you will help customers understand the value proposition of the Cloudflare Developer Platform and demonstrate how to effectively build applications with our products. 

Every day as a Solution Architect is different. You will utilize both technical and business skills to advise customers and sales teams, support strategic opportunities, architect innovative solutions, and develop proofs of concept / demonstrations. Your technical knowledge of Cloudflare’s products and system design will be vital to designing solutions that meet our customers’ needs and expectations.

Serving as a trusted technical advisor, Solution Architects guide and enable clients, partners, and teams within Cloudflare on product capabilities, positioning and competitive intelligence. You will form a tight feedback loop with product, product marketing, and technical pre-sales to refine and evolve our products. 

The ideal candidate possesses a consultative mindset, demonstrable success working with customers, and deep, practical knowledge of modern web technologies, cloud architecture, and experience building on a distributed serverless platform. No matter your background, you have natural curiosity and desire to solve problems, achieve goals, and design the most elegant and efficient solutions to address client needs. A successful Solution Architect at Cloudflare is able to act as a trusted advisor for our customers, while balancing the technical and business needs of the role – actively building and regularly presenting technical solutions to varied audiences.

Responsibilities

• Partner with the sales organization to drive revenue, new customers and pipeline of AI and Developer Platform solutions. 
• Lead technical discovery with customers and jointly architect best practice solutions to meet customer needs.
• Collaborate with cross-functional teams including product management, sales, and marketing to drive developer platform revenue and customer adoption.
• Present to strategic customers as an expert of our Developer Platform solutions.
• Align Director and C-Level perceived business and technical value with Cloudflare developer solutions.
• Provide succinct feedback to cross-functional teams to deliver relevant Developer content, use cases, customer stories, and data driven value propositions.

Skill Requirements

• 5+ years of experience selling or supporting technical sales in the cloud computing industry.
• Deep technical expertise across cloud infrastructure and AI/ML — you have built production systems that combine both as a solutions engineer, entrepreneur, or solution architect.
• In-depth knowledge of at least one major public cloud provider (e.g., AWS, GCP, Azure).
• Practical knowledge and experience designing systems. You have built and deployed a production web application either professionally or as a hobbyist and are able to clearly articulate the design and explain the considerations / trade-offs. You are able to hear a clear, non-technical description of an application, ask clarifying questions, and quickly design a high-level, conceptual architecture.
• Software development experience delivering full-stack applications, preferably using modern JavaScript frameworks, a variety of databases, and Serverless tooling. Experience building with modern coding assistants.
• Strong understanding of developer workflows (branching, versioning, CI/CD practices, system integrations).
• Knowledge of key market players/competitors in the cloud computing, AI and storage spaces.
• Up to 30% travel.

Other desirable skills areas include:

• You’ve built something on Cloudflare Workers.
• AWS Solutions Architect or GCP Cloud Architect certifications
• Providing structured customer feedback to influence product direction.
• Actively stay up-to-date with industry trends and advancements in cloud computing to inform product strategy and roadmap.

Compensation
Compensation may be adjusted depending on work location. 
This role is eligible to earn incentive compensation under Cloudflare’s Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan.

For Bay Area based hires: Estimated annual salary of 212,000.00 - 292,000.00

Equity
This role is eligible to participate in Cloudflare’s equity plan.

Benefits
Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave

Available Locations: San Francisco, CA

About the Role

Cloudflare’s Senior Forward Deployed Engineers (FDEs) operate at the intersection of product engineering and customer impact.

As an FDE, you will be embedded within one of Cloudflare’s most strategic global customers, working side-by-side with their engineering teams to build and deploy solutions using Cloudflare’s platform. Unlike traditional Solutions Architects or consultants, you will write production code, shape technical architecture, and directly influence how Cloudflare products are used at massive scale.

You will operate as a technical extension of both organizations - helping the customer ship faster while surfacing real-world product insights back to Cloudflare engineering.

This role is ideal for engineers who want to:

• Stay deeply technical
• Work on real production systems
• Influence product direction
• Build long-term partnerships with world-class engineering teams

Responsibilities

• Deep Technical Embedding: Serve as the dedicated, long-term technical partner within a strategic customer’s engineering organization, operating as a trusted extension of their team.
• Production-Level Engineering: Design, build, and deploy production-ready code and configurations directly into customer infrastructure using the Cloudflare platform.
• Technical Accountability: Own the account's technical success across the entire Cloudflare portfolio. Serve as the primary technical point of contact, with other Cloudflare technical resources taking direction from your technical strategy for the account.
• Operational Integration: Participate in customer engineering rituals, including daily standups, design reviews, and real-time incident response.
• Platform Advocacy & Adoption: Identify opportunities to accelerate the adoption of Cloudflare services, unlocking new capabilities across the customer’s tech stack.
• Platform Breadth & Depth: Deep technical competence in building production applications on a modern stack, combined with the willingness and ability to go deep on all Cloudflare product areas. From Workers to security, networking, and observability.
• Feedback Loop & Product Influence: Surface real-world edge cases and product gaps directly to Cloudflare’s Product and Engineering teams to influence the developer platform roadmap.
• Strategic Relationship Management: Establish and maintain trusted technical relationships with senior leadership (Staff+ engineers, Directors, and VPs).
• On-Site Presence: Maintain a regular on-site presence at customer locations to foster deep collaboration and cultural alignment.

Requirements

• Proven Engineering Pedigree: 7+ years of professional software engineering experience. You are a builder at heart, with a track record of delivering production-grade systems, not just advising on them.
• Production Ownership & Operational Maturity: You have owned mission-critical services with real-world users. You understand the gravity of on-call rotations, the urgency of incident response, and the architectural rigor required to maintain "five nines" uptime.
• Active Practitioner: You are currently in the IDE. You have a "ship-first" mentality and maintain a high velocity, staying current with modern frameworks, languages, and deployment patterns.
• Full-Stack Architectural Depth: Broad technical fluency across the entire stack—from frontend performance and backend logic to database optimization and distributed infrastructure.
• AI-Native Development: You have integrated AI-augmented workflows (e.g., Windsurf, OpenCode) into your daily development cycle to accelerate prototyping and delivery.
• Systems Design & Strategic Thinking: Ability to decompose complex business requirements into scalable, resilient technical architectures. You can visualize the "big picture" without losing sight of the implementation details.
• Cloud Ecosystem Fluency: Deep experience with at least one major cloud provider (AWS, GCP, or Azure), including an understanding of serverless, networking, and security primitives.
• High Agency & Navigating Ambiguity: You are a self-starter who thrives in "zero-to-one" environments. You don't wait for a ticket; you identify the problem and own the solution from end-to-end.
• Executive Presence: Comfortable engaging in high-stakes technical and strategic discussions with VP-level stakeholders, with the ability to translate complex engineering trade-offs into business impact.

Nice to Have

• Direct experience building on Cloudflare Workers, or the broader Cloudflare Developer Platform.
• Previous experience at a fast-paced startup or in a customer-facing engineering role where you operated directly within a partner’s codebase.
• A visible public profile, including open-source contributions, technical blogging, or speaking engagements at industry conferences.

Compensation

Compensation may be adjusted depending on work location.

• For Bay Area based hires: Estimated annual salary of $194,000 - $266,000.

Equity

This role is eligible to participate in Cloudflare’s equity plan.

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

About the Role

Anthropic manages one of the largest and fastest-growing accelerator fleets in the industry — spanning multiple accelerator families and clouds. The Accelerator Capacity Engineering (ACE) team is responsible for making sure every chip in that fleet is accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.

You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.

What This Team Owns

The team’s work spans three functional areas. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data infrastructure — collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against. Correctness, completeness, and latency matter here.

• Fleet observability — making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation. The work sits at the intersection of Kubernetes operations and cross-team coordination.

• Compute efficiency — measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

• Internal compute tooling — building the platforms and interfaces that make capacity data usable across the org. This includes capacity planning tools, workload attribution systems, cost dashboards, and self-service APIs. The consumers are research engineers, infrastructure teams, finance, and leadership — each with different needs and different levels of technical depth. The work involves product thinking as much as engineering: figuring out what people actually need, defining schema contracts, and making the data discoverable.

You will be placed on a pod based on your background and interests. We are especially focused on hiring for Data Platform, but strong candidates for any of the three active pods will move forward.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery. Own data completeness, latency SLOs, gap detection, and backfill automation.

• Develop and maintain observability infrastructure — Prometheus recording rules, Grafana dashboards, and alerting systems — that surface actionable signals about fleet health, occupancy, and efficiency.

• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads. Build benchmarking infrastructure, establish per-config baselines, and work with system-owning teams to improve utilization.

• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging. The consumers are other engineering teams, finance, and leadership — not external users.

• Operate Kubernetes-native systems at scale — deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.

• Normalize and reconcile data across heterogeneous sources — including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

• Collaborate across organizational boundaries with research engineering, infrastructure, inference, and finance teams. Gather requirements from technical stakeholders, translate them into useful systems, and communicate trade-offs to non-technical audiences.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems. You write code every day — this is a hands-on engineering role, not a planning or coordination role.

• Kubernetes fluency at operational depth — you’ve operated production K8s at meaningful scale, not just written manifests. Comfort with scheduling, taints, labels, node management, and debugging cluster-level issues.

• Data pipeline engineering experience — designing, building, and owning the full lifecycle of production data pipelines. Experience with data warehouses (BigQuery preferred), schema management, streaming ingestion, SLOs for latency and completeness, and a strong instinct for correctness.

• Observability tooling experience — Prometheus, PromQL, and Grafana are in the critical path for this team. Experience writing recording rules, understanding metric semantics, and building monitoring systems that engineering teams actually rely on.

• Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable.

• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level — compute, billing, usage APIs, cost management tooling. Multi-cloud experience is a strong plus.

• High autonomy and strong cross-team communication. You can gather your own requirements, navigate ambiguity, and work across organizational boundaries. Scrappiness and ownership matter more than polish.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience — especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats. Experience normalizing data from external providers with different billing arrangements is directly applicable.

• Accelerator infrastructure familiarity — GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.

• Performance engineering and benchmarking experience — building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.

• Data-as-product thinking — experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just building pipelines, but thinking about how platform data gets consumed.

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or large-scale ML environment. FinOps, chargeback systems, or infrastructure cost modeling.

Familiarity with ClickHouse, Terraform, or Rust. ClickHouse is the team’s current streaming store; Terraform for infrastructure-as-code; Rust for high-performance data collection agents.

About Us

At Prenuvo, we are on a mission to flip the paradigm from reactive “sick-care” to proactive health care. Our award-winning whole body scan is fast (under 1 hour), safe (MRI has no ionizing radiation), and non-invasive (no contrast). Our unique integrated stack of optimized hardware, software, and increasingly AI, coupled with the patient-centric experience across our domestic and global clinics, have allowed us to lead the change against “we caught it too late again".

We're looking for a Senior Frontend Engineer to join our eCommerce team, focusing on optimizing user experience, reducing friction in booking flows, and driving growth through continuous experimentation. You will be a key contributor to our online booking platform—a critical, revenue-driving application that guides customers through scan selection, scheduling, and payment. If you have a startup mentality, a passion for data-driven decisions, and the technical depth to own features from concept to production, this is a high-impact role that directly influences conversion rates, customer satisfaction, and core business metrics.

Help reshape the world through proactive healthcare while working with cutting-edge technology and high performing teams with deep expertise - join us to make a difference in people’s lives!

What You’ll Do

• Optimize the User Experience: Identify and eliminate friction points in the booking funnel, optimize page load performance, and ensure WCAG accessibility compliance across all flows.
• Drive Experimentation & Growth: Design, implement, and analyze A/B tests using a platform like PostHog or DataDog. Build feature flag infrastructure for gradual rollouts and track conversion metrics at each stage of the funnel.
• Own Frontend Architecture: Build highly responsive interfaces using a hook-first architecture (separating business logic from presentational components) and modern state patterns (optimistic updates, single-flight request patterns).
• Ensure Reliability & Observability: Set up and maintain Datadog RUM dashboards, implement comprehensive error tracking, and debug production issues to maintain high system reliability.
• Champion Testing & Quality: Write and maintain robust E2E tests (Playwright) for critical booking flows and ensure high component test coverage (Vitest, React Testing Library).
• Implement Secure Integrations: Build secure authentication flows (Auth0, OAuth 2.0) and handle payment processing data (Stripe, Affirm) according to strict PCI and frontend security standards.
• Collaborate & Mentor: Work autonomously while surfacing blockers early. Mentor junior engineers, partner closely with Product and Design, and comfortably challenge product decisions using data.

What You’ll Bring

• 5+ years of professional frontend software engineering experience, with a deep understanding of React (React 19 preferred, including hooks and functional components).
• Strong proficiency in TypeScript (strict mode, generics, type safety).
• Solid experience with modern state management (Zustand, TanStack Query) and utility-first CSS (Tailwind).
• A strong track record of writing, maintaining, and debugging automated tests using Playwright, Vitest, and React Testing Library.
• Hands-on experience with monitoring and experimentation tooling (Datadog RUM, PostHog, or similar).
• A data-driven, user-focused mindset: you empathize with customer pain points and make decisions based on metrics rather than opinions.
• A strong "startup mentality": you are comfortable with ambiguity, know how to balance speed with quality, and take deep ownership of outcomes.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Nice to Have

• Experience with e-commerce, checkout flows, or headless commerce platforms (e.g., CommerceTools).
• Experience with design systems and mobile-first design implementation.
• Experience with component libraries (e.g., Material UI) and implementing mobile-first design systems.
• Deep performance optimization expertise (Core Web Vitals, bundle optimization).
• Knowledge of Google Tag Manager (GTM) and Google Analytics 4 (GA4).
• Experience with Next.js (App Router, SSR/SSG patterns).
• Familiarity with healthcare or heavily regulated industries.

Our Values

First: we are Pioneers

• Transforming healthcare requires divergent thinking, bias for action, disciplined experimentation, and consistent grit and determination to maintain momentum. This journey is as challenging as it is rewarding.

Second: we are Platform-Builders

• We’re always building foundations that allow us to achieve tomorrow more than we did today. We never lose sight of what’s ahead – in a mindset of ownership and duty to our mission.

Above all: we are Patients

• We could all be the next person who walks through our very doors, seeking clarity or peace of mind. We are proud of our impact on our patients’ lives, and we won’t stop till everyone can benefit from our work.

What We Offer

• An avenue to make a positive impact on people's lives and their health
• We believe in preventative healthcare for everyone, including our team - Prenuvo provides free, whole-body scans to each team member 
• Growth opportunities are at the heart of our people journey, we’re doing big things with bright minds - there is no single path to success, it can be shaped along the way
• Building strong relationships is at the core of everything we do - our team gets together each week to connect, share, and socialize 
• Recognizing time away to restore is vital to our wellbeing - we have a flexible vacation policy and we will encourage you to use it
• We now offer the Prenuvo’s Commuter Benefits Plan to help cover your transit and parking costs. Whether you ride, drive, or park, we’ve got you covered—making your commute easier and more affordable! 
• Prenuvo offers a 401(k) retirement savings plan to eligible employees, allowing team members to make pre-tax contributions toward their retirement. While Prenuvo facilitates access to the plan, the company does not currently offer matching contributions.
• We offer a comprehensive benefits package including health, dental, vision, including Mental Health coverage, to support you and your family
• The base salary for this role is $175,000 to $190,000 in local currency, depending on experience and geographic location

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

As part of the hiring process, successful candidates will undergo a background check in compliance to applicable federal, provincial, and state rules.

Please be advised that official communication from our recruitment team will only come from our authorized domain [prenuvo.com]. If you are contacted by a recruiter, please ensure their email address ends with @prenuvo.com. We do not use third-party recruitment services or any other email domains for hiring purposes. If you receive communication that you believe to be fraudulent, please report it immediately to jobs@prenuvo.com.

We are looking for a Functional Safety Software Engineer to join us and drive the development and management of our autonomous vehicle safety cases as we bring the Kodiak Autonomy System to market. We first published our Safety Report in 2019 and have based our development on systems engineering, the ISO26262 process and SOTIF principles. 

In this role, you will:

• Participate in developing technical safety requirements to be used in the Kodiak Autonomy System in various approved Operational Design Domains. 
• Lead specification of software safety requirements.
• Participate in development of software safety architectural design.
• Participate in software safety unit design and implementation.
• Develop test plans, test procedures, verification reports at the software unit and software integration levels. Support system level testing from a software safety perspective.
• Perform software safety analyses (e.g. dependent failure analysis) to comply with ISO 26262.
• Support Hardware-Software Interface development and derive safety measures.
• Collaborate with Kodiak internal and external stakeholders to review and assess work products for compliance with ISO 26262.
• 10% travel to test sites possible

What you’ll bring:

• Bachelor’s degree or higher in software, electrical, mechanical or other related engineering and/or a Bachelor’s degree with professional experience in a high tech environment
  
• Experience with Part 4, 6, 8 and 9 of ISO 26262. Special emphasis on implementation of Part 6 for autonomous vehicles  
  
• Experience with developing work products for safety critical systems. 
  
• Experience with system and software level verification and validation of autonomous vehicles
  
• Experience with functional safety standards such as ISO26262, SOTIF, and UL4600.
  
• Good communication skills with a collaborative approach
  
• Ability to structure project tasks and drive evidence development among teams
  
• Knowledge of software configuration management and software quality assurance
  

What we offer:

• Competitive compensation package including equity and biannual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Anthem, and Guardian (including a medical plan with infertility benefits)
• Flexible PTO and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace, One Medical, Gympass, Spring Health
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

The role 

Nebius is building the cloud infrastructure that will power the next generation of Physical AI—robotics, autonomous systems, simulation/world models, and embodied intelligence operating in the real world.

The Field CTO for Physical AI & Robotics is a senior technical leadership role responsible for converting raw market demand into a scalable, domain-specific platform. You will own the technical product strategy, ensuring Nebius evolves its capabilities to support the unique demands of Physical AI workloads. Operating at the intersection of deep customer engagement and platform engineering, you will serve as a principal technical partner in strategic opportunities—engaging directly with customer CTOs to map Nebius’ existing capabilities to their immediate needs to help close complex deals. You will not only identify customer challenges but also architect the solution patterns that solve them for the entire market.

This is a definitive "Zero to One" opportunity to define a new category of cloud infrastructure from the ground up.

You’re welcome to work remotely from the Unites States (SF Bay Area, CA & Austin, TX Preferred)

Your responsibilities will include: 

• Executive Technical Leadership: Serve as the external "CTO" face of Nebius to Physical AI customers, partners, and ecosystem stakeholders, building trust with executive peers.
• Lighthouse Deal Support: Partner with Sales leadership to close strategic "company-making" deals by leading architectural workshops and aligning technical roadmaps with customer goals.
• Technical Product Strategy: Translate bespoke customer needs into clear, scalable technical and product requirements for Nebius product, engineering, and infrastructure teams.
• Field Enablement: Act as a force multiplier for the sales organization by creating the technical narrative, reference architectures, and training materials needed to upskill Field SAs and Sellers.
• Cross-Functional Alignment: Drive alignment across Product, Engineering, Infrastructure, and GTM teams, ensuring the internal roadmap reflects the reality of the market.
• Architectural Guidance: Provide architectural guidance to help customers maximize value from Nebius services, while identifying the necessary "primitives" required to support end-to-end robotics workflows.
• Pattern Recognition: Identify recurring customer pain points across robotics, simulation, and data pipelines to surface gaps in existing offerings and influence roadmap decisions.
• Ecosystem & M&A: Partner with ecosystem vendors (simulation platforms, robotics frameworks) to identify integration opportunities and evaluate potential technical M&A targets.
• Feedback Loops: Maintain structured internal feedback loops to ensure customer learnings are tracked, communicated, and acted upon by R&D. 

We expect you to have: 

• 10+ years of experience in cloud infrastructure, platform engineering, or distributed systems.
• 5+ years of experience in AI, HPC, and/or robotics, with exposure to production or large-scale systems.
• Prior experience in a senior technical leadership role (e.g., Field CTO, Head of Engineering, Principal Architect, or Distinguished Engineer).
• Dual-Competency: You are equally comfortable drawing a distributed system architecture on a whiteboard for engineers and explaining the business value of that architecture to a CEO.
• GTM Fluency: Experience partnering with Sales teams to close large-scale enterprise deals and enabling field teams with technical assets.
• Product-Minded Leadership: Experience defining a product or platform strategy based on market feedback, not just executing technical tickets.
• Technical Depth: Strong hands-on understanding of GPU-centric infrastructure, high-performance compute, storage systems, and networking.
• Robotics Fluency: Experience with Physical AI and robotics workflows, including simulation, synthetic data, training pipelines, and real-world deployment constraints.
• Communication: Strong executive presence, capable of influencing product teams and leadership through clarity and credibility.
• Comfort in Ambiguity: Experience operating in fast-moving environments (hyperscalers, cloud platforms, or advanced AI startups) where requirements are evolving. 

Why Nebius:

• Build Solutions: You aren't just selling infrastructure; you are shaping the cloud architecture that will power the next generation of Physical AI
• Frontier Technology: Work at the frontier of AI, simulation, and real-world intelligence alongside leading customers and partners
• Strategic Impact: Operate with real influence over product direction, platform strategy, and ecosystem development
• Ownership: Join a team that values technical depth, ownership, and speed of execution
• Mission: Help define how intelligence moves from the data center into the physical world

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
• Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Are curious about LLM serving; prior inference or ML experience is not required
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• Have experience working with external partners to align goals and deliver impact
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

OUR COMPANY:

EOS IT Solutions is a Global Technology and Logistics company, providing Collaboration and Business IT Support services to some of the world’s largest industry leaders, delivering forward-thinking solutions based on multi-domain architecture. Customer satisfaction and commitment to superior quality of service are our top business priorities, along with investing in and supporting our partners and employees.

We are a true International IT provider and are proud to deliver our services through global simplicity with trusted transparency.

WHAT YOU WILL DO:

We are looking for a skilled and detail-oriented AV Commissioning Engineer to lead the testing, configuration, and fine-tuning of complex audio-visual systems. In this role, you’ll collaborate with cross-functional teams to ensure AV systems are delivered to the highest quality standards and meet client expectations. This is an excellent opportunity for a hands-on AV professional with strong technical acumen and a passion for delivering world-class AV experiences.

KEY RESPONSIBILITIES:

• Collaborate with project teams to review and understand AV designs and specifications
• Perform on-site testing and commissioning of AV systems, ensuring full functionality
• Configure, program, and integrate AV components including displays, projectors, audio processors, and control systems
• Calibrate AV systems for optimal audio and video performance (levels, resolutions, color accuracy)
• Troubleshoot and resolve technical issues during commissioning and handover
• Validate signal flow and connectivity across all AV components
• Implement and test AV control systems (touch panels, automation, user interfaces)
• Document configuration settings, commissioning results, and system adjustments
• Provide training and operational support to end-users and clients
• Partner with designers and programmers to optimize system performance and user experience

ESSENTIAL CRITERIA:

• Previous experience in AV commissioning or a similar technical AV role
• Strong understanding of AV hardware and protocols (HDMI, HDBaseT, Dante, AES67)
• Proficient in AV calibration techniques and the use of testing tools (e.g., signal generators, analyzers)
• Familiarity with AV control and DSP platforms such as Crestron, Extron, Biamp, or QSC
• Exceptional troubleshooting and diagnostic skills
• Excellent written and verbal communication skills
• Detail-oriented and highly organized, with a commitment to high-quality delivery
• Able to work both independently and in a team setting
• Flexibility to travel to client/project sites as needed

DESIRABLE CRITERIA:

• Bachelor's degree in Electrical Engineering, Audio Engineering, Computer Science, or equivalent experience
• Industry certifications such as CTS (Certified Technology Specialist) 
• Experience in enterprise environments or large-scale AV deployments
• Proficiency in control system programming or GUI customization
• Familiarity with remote monitoring tools or AV over IP technologies
• Experience training end-users and conducting technical walkthroughs

EOS is committed to creating a diverse and inclusive work environment and is proud to be an equal opportunity employer. We invite you to consider opportunities at EOS regardless of gender, gender identity, gender reassignment, age, religious or similar philosophical belief, race, national origin, political opinion, sexual orientation, disability, marital or civil partnership status, or other non-merit factor.

The EOS pay range for this job is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, experience, education, knowledge, skills, and abilities, as well as internal equity, market data, or other laws. 

#LI-HH1

About the role

As a Customer Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment.

Responsibilities

• Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge Kubernetes GPU clusters; ensure swift and effective solutions every time.
• Become a product expert in our GPU Cluster service, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
• Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction.
• Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support)
• Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers.
• Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers.

Requirements

• 3+ years of experience in a customer-facing technical role with at least 1 year in a support function in AI or supporting a mission-critical API in SaaS
• Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments.
• Familiarity with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, container infrastructure, and scripting and programming languages.
• Foundational understanding in the installation, configuration, administration, troubleshooting, and securing of compute clusters.
• Complex technical problem solving and troubleshooting, with a proactive approach to issue resolution
• Ability to work cross-functionally with teams such as Sales, Engineering, Support, Product and Research to drive customer success.
• Strong sense of ownership and willingness to learn new skills to ensure both team and customer success.
• Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000-230,000K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

This is a research engineering role with direct production impact. You won’t be publishing ideas in isolation—you will translate new RL algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together’s API. Success in this role means shipping measurable improvements in latency, throughput, cost, and model quality at scale. We are looking for researchers who enjoy owning systems end-to-end and turning frontier ideas into robust infrastructure.

The Core ML (Turbo) at Together AI team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale.

Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design.

You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal.

Responsibilities

• Advance inference efficiency end‑to‑end
• Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference.
• Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc.
• Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost.
• Unify inference with RL / post‑training
• Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems.
• Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper.
• Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack.
• Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers.
• Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design.
• Own critical systems at production scale
• Profile, debug, and optimize inference and post-training services under real production workloads, taking research ideas all the way to stable, measurable improvements in deployed systems.
• Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed.
• Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously.
• Provide technical leadership (Staff level)
• Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training.
• Mentor other engineers and researchers on full‑stack ML systems work and performance engineering.

Requirements

We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay.

You might be a good fit if you:

• Have a bias toward implementation and shipping—you are excited to modify real engines and services, not just prototype in research code.
• Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others:
• Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving.
• RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models.
• Model architecture design for Transformers or other large neural nets.
• Distributed systems / high‑performance computing for ML.
• Are comfortable working from algorithms to engines:
• Strong coding ability in Python
• Experience profiling and optimizing performance across GPU, networking, and memory layers.
• Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack.
• Have a solid research foundation in your area(s) of depth:
• Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems).
• Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API).
• Operate well as a full‑stack problem solver:
• You naturally ask: “Where in the stack is this really bottlenecked?”
• You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins.

Minimum qualifications

• 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source).
• Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience.
• Demonstrated experience owning complex technical projects end‑to‑end.

If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

We’re hiring a Support Leader to own and scale Together AI’s customer support function across two distinct, technically demanding domains: API Support (billing, serverless inference, and dedicated inference) and GPU Support (large-scale GPU infrastructure for model training workloads). You’ll work closely with Together AI’s VP of Customer Experience and partner tightly with SRE, Inference Platform, and Engineering to represent customers internally and drive resolution at speed. This is a player-coach role: you’ll be hands-on in escalations. 

Our support operation runs 24/7. Our GPU infrastructure customers hold us to high-stakes SLAs on training workloads. Our API customer base spans thousands of PLG and enterprise accounts relying on our serverless and dedicated inference endpoints. Both domains need a leader who can keep pace technically and build the operational muscle to scale.

Responsibilities

Team Leadership and Mentorship

• Directly manage and develop a team of support engineers and technical account specialists across API Support and GPU Support functions.
• Establish clear performance expectations, career growth paths, and a coaching culture leveraged to identify skill gaps and build training programs to close them.
• Run structured 1:1s, team reviews, and escalation retrospectives.

Operationalization and Scaling

• Assess and overhaul support workflows, SLA frameworks, and escalation playbooks
• Build triage, prioritization, and handoff protocols that allow the team to scale with customer growth without proportional headcount growth.
• Define and own support KPIs: SLA attainment, time-to-resolution, escalation rate, CSAT

GPU Infrastructure Support (Hands-On)

• Jump into complex, active GPU infrastructure issues alongside your team. Investigate NCCL and InfiniBand failures, SSH connection stalls, Kubelet TLS misconfigurations, GPU/RDMA provisioning timeouts, NFS RDMA mount failures, VAST storage failures, network fabric degradation, etc.
• Manage high-stakes SLA obligations with GPU cloud customers running multi-thousand-GPU training workloads
• Coordinate closely with SRE and infrastructure engineering on hardware-level issues and cluster bringup.

 API and Inference Support (Hands-On)

• Own the support surface for Together AI’s API platform: serverless inference, dedicated inference endpoints (self-serve and managed), billing, rate limits, model upload (BYOM), and API authentication.
• Represent the team on complex cases: dedicated endpoint startup failures, safetensors validation errors, NFS/storage performance issues on inference clusters, billing disputes and negative-balance enforcement, and rate limit escalations.
• Work with the Inference Platform, Commerce, and Product teams to surface patterns and drive fixes upstream.

Escalation and Cross-Functional Partnership

• Be the escalation point for your team’s highest-severity customer issues — triage fast, communicate clearly to customers and internal stakeholders, and drive to resolution.
• Partner with SRE, Engineering, and Sales on shared priorities. Represent the support team’s perspective in cross-functional planning.
• Own the relationship with support tooling vendors and drive improvements to alerting, SLA tracking, and ticket routing.

Customer Feedback Loop

• Systematically analyze ticket patterns and surface product and infrastructure gaps to Engineering and Product. Turn support signal into actionable roadmap input.
• Build documentation and self-service resources that reduce inbound volume over time.

Requirements

• 10+ years of support engineering or technical support leadership experience, with at least 3 years managing a team.
• Demonstrated experience leading infrastructure support or cloud operations. You understand how large-scale workloads behave on distributed systems. 
• Working knowledge of AI infrastructure. You know how APIs work, can reason about latency and throughput issues, and understand the operational surface of a managed inference platform.
• Technical depth to be a credible player-coach. Ability to guide engineers through root cause analysis, and bring credibility to customer-facing escalations.
• Experience running SLA-driven support operations with real accountability. Familiarity with Pylon or equivalent support ticketing platforms (Zendesk, etc.) and PagerDuty-style alerting systems.
• Strong communication skills, especially under pressure. You can write a clear, concise customer-facing update in the middle of a live incident and distill a complex infrastructure issue into a crisp internal escalation.
• Startup mindset. You’re comfortable building process where none exists, and you thrive in environments where priorities shift fast.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $290,000 - $310,000K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our Privacy Policy at https://www.together.ai/privacy

About the role

As a Forward Deployed Engineer (FDE) focused on large scale GPU clusters, you will be a hands-on technical partner to our strategic customers – the world’s leading AI model builders. You will partner with our SAs as a deep-domain specialist in large-scale infrastructure, storage, high-performance networking, and cluster orchestration. As key contributors to the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption for our strategic customers, and guide tailored optimization efforts - directly impacting company growth and the hardening of our core platform.

Responsibilities

• Cluster Hardening & Validation: Design and execute rigorous pre-handover test suites (NCCL, DCGM, GPU Burn) to ensure clusters are stable under the extreme stress of multi-node training.
• Technical Partnership: Act as the primary technical point of contact for model labs, helping them tune their orchestration layer (Kubernetes or SLURM) for maximum throughput.
• Infrastructure Optimization: Profile and debug low-level bottlenecks in InfiniBand (IB) fabrics, NVLink topologies, and high-performance storage systems.
• Opinionated Onboarding: Build reference designs and "out-of-the-box" configurations for training frameworks to reduce customer time-to-train.
• Benchmarking & Migration: Lead complex benchmarking exercises to demonstrate the performance impact of migrating to new hardware families or Together AI’s optimized infrastructure.
• Product Feedback Loop: Directly influence our hardware and software roadmap by surfacing edge cases and performance gaps found during customer deployments.

Requirements

• Experience: 5+ years in a technical role, with a strong focus on Large-Scale GPU Infrastructure.
• Orchestration Mastery: Deep, hands-on experience with Kubernetes (specifically GPU-operator and device plugins) and/or SLURM for workload scheduling.
• Networking & Interconnects: Expert knowledge of InfiniBand, RoCE, and NVLink; ability to diagnose network failures that degrade collective communication (NCCL).
• Storage Knowledge: Familiarity with parallel file systems (VAST or Weka preferred) and object storage, specifically in the context of large-scale checkpointing.
• Benchmarking Skills: Ability to run and interpret training benchmarks and communication tests to validate cluster health and performance.
• Coding & Automation: Proficiency in Python and shell scripting; experience with Ansible or similar tools for automated cluster configuration.
• Willingness to dive into the customer's stack to solve hard problems and comfortable with the high-stakes, fast-paced environment of frontier model labs.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!

Responsibilities

• Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
• Develop and optimize runtime inference services for large-scale AI applications.
• Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
• Conduct design and code reviews to ensure high standards of quality.
• Create services, tools, and developer documentation to support the inference engine.
• Implement robust and fault-tolerant systems for data ingestion and processing.

Requirements

• 3+ years of experience writing high-performance, well-tested, production-quality code.
• Proficiency with Python and PyTorch.
• Demonstrated experience in building high performance libraries and tooling.
• Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
• Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
• Preferred: Knowledge of AI inference techniques such as speculative decoding.
• Preferred: Knowledge of CUDA/Triton programming.
• Nice to have: Knowledge of Rust, Cython and compilers.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

About the Role

Together AI is looking for an ML Engineer who will develop systems and APIs that enable our customers to perform inference and fine tune LLMs. Relevant experience includes implementing runtime systems that perform inference at scale using AI/ML models from simple models up to the largest LLMs.

Requirements

• 5+ years experience writing high-performance, well-tested, production quality code
• Bachelor’s degree in computer science or equivalent industry experience
• Familiar with LLM inference ecosystem, including frameworks and engines (e.g. vLLM, SGLang, TRT, ...)
• Demonstrated experience in building large scale, fault tolerant, distributed systems like storage, search, and computation
• Expert level programmer in one or more of Python, Go, Rust, or C/C++
• Experience implementing runtime inference services at scale or similar

Responsibilities

• Design and build the production systems that power the Together Cloud inference and fine-tuning APIs, enabling reliability and performance at scale
• Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world
• Analyze and improve efficiency, scalability, and stability of various system resources
• Conduct design and code reviews
• Create services, tools & developer documentation
• Create testing frameworks for robustness and fault-tolerance
• Participate in an on-call rotation to respond to critical incidents as needed

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $220,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the role

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform.

Responsibilities

• Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile
• Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets.
• Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production.
• Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.
• Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value.
• Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos.

Qualifications

• Experience: 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows.
• Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level.
• Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques
• Post-Training Knowledge: Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO; ability to advise on system design
• Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets.
• Coding Proficiency: Strong Python skills; comfortable working in production environments

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

Together AI is building the Inference Platform that powers the world's most advanced generative AI models. Your role will be a critical bridge between cutting-edge research and real-world applications, focusing on making translating our internal model training research to production-ready deployment for our customers. This involves a deep commitment to data-centric development, meticulous hyperparameter tuning, and rigorous checkpoint evaluation before models ever hit production.

This role will involve understanding customer specific needs and fine-tuning models on our internal data recipe and their proprietary data. The goal is to transform general-purpose models into highly performant, specialized tools that solve real business problems. You will not be training foundation models from scratch but rather focusing on creating highly efficient, specialized models by working with dedicated GPU clusters.

Responsibilities

• Design and iterate on novel speculator algorithms, combining architectural innovations with carefully curated data to push the frontier of accuracy–efficiency tradeoffs.
• Be the critical link between raw data and a production-ready model, seeing your work directly impact our customers' success.
• Work in a fast-paced, high-impact role at the cutting edge of generative AI.
• Collaborate with a team of experts dedicated to solving real-world, high-performance challenges.
• You'll collaborate directly with customers to understand their needs, and work closely with our core inference and Applied ML research teams to integrate your work into the production platform.
• A culture of deep technical ownership where you are empowered to take on and solve challenging problems

Requirements

• A genuine love for data curation and processing, with a meticulous attention to detail. You believe that great models start with great data.
• Demonstrated ability to perform effective hyperparameter searches and understand the trade-offs involved in tuning models for specific tasks.
• Experience working with and building on top of existing training codebases. You are comfortable navigating complex code and contributing to its improvement.
• Strong attention-to-detail in evaluating model checkpoints to ensure they meet strict quality, performance, and reliability standards.
• Experience with Python and PyTorch.
• Familiarity with SLURM and/or Kubernetes clusters and experience submitting and managing jobs in a high-performance computing environment.
• Familiarity with modern LLMs and generative models.
• Basic understanding of distributed training frameworks (e.g., FSDP, DeepSpeed).
• Bachelor’s, Master’s degree, or Ph.D. in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, ATLAS, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

Requirements

• Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
• Knowledge of ML/AI applications and models
• Knowledge of performance profiling and optimization tools for GPU programming
• Excellent problem-solving and analytical skills
• Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences

Responsibilities

• Optimize and fine-tune GPU code to achieve better performance and scalability
• Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
• Stay up-to-date with the latest advancements in GPU programming techniques and technologies

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

Staff Engineer — API Core Platform

About the role

Together AI is seeking an experienced Backend Engineer to found Together’s API Platform team within the Production Foundations organization. In this role, you will define, build, and scale the core systems and architecture that power Together’s mission-critical APIs — including public customer APIs used directly by customers and via SDKs, CLIs, as well as the client APIs powering Together’s Cloud UI.

In the near term, you will improve and standardize the backend API layer within our primary Next.js monolith, raising the bar on reliability, performance, and consistency. In parallel, you will design and lead the evolution toward scalable, purpose-built next-gen API platform solutions optimized for different Public API and Client API use cases and traffic patterns — defining the long-term architecture and driving its incremental rollout.

This is a deeply hands-on role for an engineer who thrives on writing critical-path code and building platforms that unify engineering efforts across teams. You will work across backend systems, infrastructure layers, identity and access flows, and developer tooling to establish a cohesive API strategy that supports Together’s rapidly growing AI Cloud.

Responsibilities

• Design and drive the evolution of Together’s API platform, defining how APIs are built, versioned, secured, tested, and operated across the company
• Own and improve the backend API layer within our primary Next.js monolith, raising the bar on consistency, reliability, and performance
• Architect and lead the transition toward scalable, purpose-built API platforms optimized for different traffic patterns and product surfaces
• Write and maintain critical-path platform code that multiple services and product teams depend on
• Design and implement robust authentication, authorization, and identity-aware access patterns across public and internal APIs
• Establish performance standards for high-throughput APIs, implementing caching, rate limiting, fan-out control, and graceful degradation strategies
• Raise the bar on API observability and reliability, defining SLOs, monitoring, alerting, and incident response practices
• Drive API data modeling and schema generation strategies to ensure long-term maintainability and developer ergonomics
• Partner with infrastructure and security teams to maintain a strong security posture and evolve toward zero-trust architectures
• Mentor engineers, influence architectural direction across teams, and help define hiring standards as the API Platform grows

Required Qualifications

• 8+ years of experience building and operating large-scale, distributed backend systems in production environments
• Proven experience building or significantly evolving an API platform used by multiple teams or customer-facing products
• Expert-level proficiency in one or more of Golang, TypeScript, C++, or Java
• Deep expertise in API performance and scalability, including caching strategies, rate limiting, parallelization, fan-out control, and graceful degradation
• Strong experience designing and implementing production-grade authentication and authorization systems for customer-facing APIs
• Demonstrated ability to drive cross-team architectural initiatives without formal authority, aligning multiple stakeholders around long-term platform direction
• Experience building and operating systems using Infrastructure as Code (Terraform, AWS CDK, Pulumi) and modern CI/CD workflows
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or equivalent practical experience

Nice to Have

• Experience with GraphQL or schema-based API federation systems
• Experience evolving APIs from monoliths to modular, platform-oriented architectures
• Experience designing and operating API schema generation and validation systems
• Experience building developer-facing SDKs or command-line tools
• Experience designing and operating multi-region, globally distributed API systems
• Experience designing horizontally scalable API systems capable of handling high request volume and burst traffic patterns
• Experience running production workloads in Kubernetes-based environments
• Experience building services in zero-trust or identity-aware architectures
• Experience with AWS networking, traffic management, and load balancing
• Experience with Cloudflare or CDN-level API performance optimization

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy 

About the role

As a Dedicated AI Factory TAM at Together AI, you will serve as the named technical owner for one of our most strategic enterprise relationships. You will be the primary technical point of contact across all infrastructure domains — compute, networking, storage, and facilities — ensuring smooth delivery and operational health of large-scale GPU deployments. This role sits at the intersection of deep infrastructure expertise and high-stakes customer partnership, making you a critical driver of both customer success and company growth.

Responsibilities

• Serve as the named technical point of contact for a dedicated strategic customer, owning the end-to-end technical relationship across compute, networking, storage, and facilities
• Drive structured engagement through regular cadences including status reporting, technical steering meetings, and executive business reviews
• Translate customer operational feedback into actionable input for Engineering, Product, and Infrastructure roadmaps
• Lead issue lifecycle management, escalation, and RCA authorship across all infrastructure domains in partnership with Support, SRE, DC Ops, and Engineering teams
• Own end-to-end RMA coordination and hardware lifecycle management, including acceptance testing, spare inventory management, and hardware health reporting for large-scale GPU deployments
• Maintain deep technical expertise across the customer's infrastructure stack — GPU compute, high-speed fabric, and large-scale storage systems — advising on configuration, operational best practices, and incident resolution
• Own the observability strategy for the customer estate, including alert policy definition, dashboard development, and proactive health management across all infrastructure layers
• Coordinate DC operations and facilities events in partnership with internal teams and hosting providers, ensuring SLA compliance and cluster availability
• Act as project manager for all capacity expansions, owning the full node deployment lifecycle from freight receipt through production acceptance

Qualifications

• 5+ years in a customer-facing technical role, with 2+ years in dedicated technical account management or solutions architecture for large-scale AI or HPC infrastructure
• Deep expertise in GPU infrastructure — GPU health diagnostics, RMA workflows, and hardware acceptance testing
• Hands-on experience with large-scale Ethernet and InfiniBand fabric architecture
• Working knowledge of enterprise storage systems, including high-density NVMe, parallel file systems, and metadata infrastructure
• Experience with DC operations, facilities coordination, and hosting provider SLA management
• Strong ownership mindset for incident management, RCA authorship, and executive-level customer communication
• Proficiency in infrastructure monitoring and observability tooling (Prometheus, Grafana, or equivalent)
• Proven ability to manage multiple concurrent workstreams with hyperscaler-level rigor and communication standards
• Proficiency in Python, Bash, or infrastructure automation tools preferred

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $260-290K OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Location

San Francisco, CA (Hybrid) or New York, NY (Hybrid)

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy

About the Role

Our team focuses on enabling custom models and dedicated inference on Together. We are responsible for building a container platform, optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. We often focus on video or audio generation across the stack: CUDA kernels, pytorch optimization, inference engines, container orchestration, queueing theory, etc. An ideal candidate will be great at profiling/optimization but know the word kubernetes, or be intimately familiar with multi-cluster scheduling and have some sense of ML bottlenecks.

Responsibilities

• New hires may work on multi-cluster orchestration, portfolio optimization, predictive autoscaling, control panes, model bring-up, model optimization, APIs for managing deployments, inference worker SDKs, and CLI tools.
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems.
• Experience running serverless inference platforms, doing model bring-up on short notice, being on call, or running a cloud provider is a very big plus
• Good taste and ability to thoughtfully discuss how what you’ve built has failed over time
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent understanding of low level operating systems concepts including concurrency, networking and storage, performance and scale
• Expert-level programmer in one or more of Python, Golang, Rust, C++, or Haskell
• Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform
• Experience with Kubernetes internals or other container orchestration systems
• Sound judgement for when to use and when to not use LLMs for code
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Writing-heavy roles or companies are a plus

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As a Senior Infrastructure Technical Program Manager (TPM) at Together AI, you will be at the core of building, optimizing, and scaling the global GPU resources needed for a pioneering AI infrastructure company. Your role is crucial in ensuring that the backbone of our AI models, thousands of GPUs distributed around the world, operates efficiently and reliably, enabling cutting-edge AI advancements that democratize access to AI technology globally.  You will drive cross-functional excellence by streamlining critical workflows and enhancing communication across internal and external teams. Join top engineers, researchers, and innovators to shape the future of AI infrastructure and power the next generation of AI-driven solutions.

Responsibilities

• Product Development: Design and build products for AI researchers, developers, and enterprise customers, translating technical requirements into product features and collaborating with research, engineering, and design teams. Develop and execute strategic plans for the Observability, Storage, Network Engineering, and Security infrastructure teams.
• End-to-End Product Ownership: Own a comprehensive product roadmap, detailing key features, enhancements, and releases. Drive end-to-end product development, manage development and testing, and lead launches.
• Stakeholder Engagement: Engage with stakeholders to understand their needs, pain points, and feedback. Drive initiatives to enhance customer satisfaction and loyalty through product improvements and innovative solutions.
• Cross-Functional Execution: Lead and align diverse cross-functional teams — including Research, Engineering, DevOps, SRE, and Go-to-Market — to ensure seamless project delivery and organizational success.

Requirements

• ML Product or Infrastructure Experience: 5+ years of experience building and scaling AI/ML-powered products and infrastructure, specifically collaborating with research and engineering teams.
• Proven experience with large-scale technology deployments, including cloud computing platforms, decentralized cloud infrastructure, and distributed systems (e.g., containerization and orchestration tools).
• Familiarity with the technical domains of Observability, Storage, Network Engineering, and Security for infrastructure.Experience with cloud computing platforms, decentralized cloud infrastructure, and/or similar large-scale technology deployments.
• Familiarity with cloud-based technologies (e.g., AWS, Google Cloud, or Azure)
• Technical Foundation: Bachelor's or Master's degree in Machine Learning, Computer Science, Engineering, or a related field.  
• Exceptional analytical and problem-solving skills, with a demonstrated ability to identify and proactively mitigate technical risks
• Experience using AI tools, such as ClaudeCode or similar, to accelerate analytical progress.
• Executive and Organizational Acumen
• Proven ability to thrive in a fast-paced, ambiguous startup environment, prioritizing complex tasks and managing multiple simultaneous projects.
• Strong organizational abilities to build cross-functional alignment and establish clear, focused priorities.
• A proactive and collaborative team-oriented approach, demonstrating a willingness to drive necessary outcomes across the company.
• Excellent communication and program management skills for effective collaboration with both internal stakeholders and external vendors.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $225k to 265k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. This is a hybrid role based in the Bay Area.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is looking for a Senior Data Engineer to help define, build, and operate the data infrastructure that handles millions of events every day to power Together’s mission-critical systems. As a Senior Data Engineer, you will work with our Data and Commerce engineering team to scale the data processing components of Together’s usage-based billing system, real-time customer-facing analytics product, and internal business intelligence tools. You will work across both cloud-native services and globally distributed data centers.

If you thrive in fast-paced environments and have a passion for defining and building early-stage data platforms for a rapidly scaling and data-intensive company, this is for you.

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed data platforms, stream processing pipelines, ETLs, etc
• Expert-level skills in designing, building, and operating stream processing pipelines with services like AWS Kinesis, Apache Kafka, or Redpanda
• Expert-level knowledge of building real-time customer facing analytics systems using services like AWS TimeStream or Clickhouse
• Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform, AWS CDK, or Pulumi
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Proficiency in implementing and managing GitOps workflows with tools such as ArgoCD, Github Actions, TeamCity, or similar
• Proficiency in one or more of Golang, Rust, Python, Java, or TypeScript
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Experience with Kubernetes, or containers a plus

Responsibilities

• Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
• Analyze and improve the robustness and scalability of existing data processing infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $240,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase.

You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems.

Responsibilities

• Participate in on-call rotation (Pagerduty) to respond to production incidents
• Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users
• Build monitoring systems to ensure the highest quality service for our customers
• Design and implement operational processes (such as deployments and upgrades)
• Debug production issues across all services and levels of the stack
• Identify improvements for the product architecture from the reliability, performance and availability perspectives 
• Plan the growth of Together AI’s infrastructure

Requirements

• 5+ years of professional AI Infra or related experience
• Bachelor's degree in Computer Science or a related field or equivalent work experience
• Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes
• Proficiency in programming/scripting languages
• Direct experience in monitoring and observability practices
• Knowledge of cloud services
• Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior Backend Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal StaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Some of what you’ll work on:

• Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters.
• Build out a global management plane for managing our data center compute, networking, and storage.
• Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features.

Responsibilities

• Identify, design, and develop foundational backend services that power Together’s cloud platform
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Demonstrated experience with building and operating high-performance and/or globally distributed microservice architectures across one or more cloud providers (AWS, Azure, GCP)
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience developing against and managing a relational database, such as PostgreSQL
• Expert-level programmer in one or more of programming language (Golang preferred)
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Experience with Kubernetes and containers preferred
• Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.

We're looking for a Senior Platform Engineer to own the API and infrastructure layer for voice workloads. You'll build the real-time WebSocket and HTTP APIs that developers use to ship voice experiences, design autoscaling for latency-sensitive streaming workloads, and ensure our multi-provider voice platform is reliable enough for production voice agents handling millions of calls.

This is a foundational hire on a small, high-impact team. Voice APIs have fundamentally different infrastructure requirements than text-based inference — bidirectional audio streaming, stateful connections, tight latency SLOs, and complex multi-model routing. You'll define how developers interact with Together's voice platform as we grow from early customers to the default infrastructure for voice AI.

• Own the real-time API layer (WebSocket + HTTP streaming) that powers Together's voice platform.
• Design autoscaling and orchestration for voice workloads running on tens of thousands of GPUs.
• Build the developer experience — APIs, observability, and tooling — for a fast-growing product area.
• Work with production voice customers (contact centers, AI agents, communication platforms) to ship what they actually need.
• Join a small, early-stage team with outsized impact on a new product line.

Responsibilities

• Build and harden real-time WebSocket and HTTP streaming APIs for STT and TTS — including connection lifecycle management, backpressure, error handling, and reconnection, at the reliability bar needed for production voice agents.
• Design and ship autoscaling for voice model endpoints that handles bursty, real-time traffic patterns — accounting for concurrent connection limits, streaming state, and hard latency ceilings.
• Implement voice-specific API features: word-level alignment, speaker diarization in realtime, audio format flexibility (g711/mulaw for telephony, PCM, WebRTC formats), pronunciation controls, and multi-context WebSocket support.
• Build voice-specific observability — latency breakdowns, audio quality signals, and dashboards that help both the team and customers debug issues.
• Own multi-model normalization across our model partners (Cartesia, Deepgram, Rime, and others), ensuring consistent API behavior regardless of the underlying provider.
• Collaborate with the ML engineering side of the team on the interface between the API layer and the model serving stack, ensuring latency and reliability requirements are met end-to-end.
• Contribute to developer experience — API design, documentation, integration cookbooks, playground and showcasing how best-in-class voice agents are built.
• Lay the groundwork for multiple new products down the line.

Requirements

• 5+ years of experience building large-scale, real-time distributed systems and API services.
• Deep expertise in real-time streaming infrastructure — WebSocket server architecture, Server-Sent Events, bidirectional streaming, connection multiplexing, and stateful protocol design.
• Expert-level programming in TypeScript and Python; experience with Rust is a plus.
• Strong distributed systems fundamentals: load balancing, autoscaling, rate limiting, and traffic shaping for latency-sensitive workloads.
• Experience with Kubernetes — including custom autoscalers, resource management, and health checking for stateful services.
• Strong product sense — you care about API ergonomics and think about what developers building voice apps actually need.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Experience with audio or media protocols (WebRTC, g711, PCM encoding) is a strong plus.
• Familiarity with ML model serving infrastructure and how inference engines work is a plus — you'll interface with the serving layer regularly.
• Full-stack experience (React, Next.js) is a nice-to-have for contributing to developer-facing tooling.
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is seeking a Staff Backend Engineer to own the technical vision, architecture, and execution of the commerce platform powering Together's Cloud products. As a staff engineer on the Commerce Engineering team, you will set the engineering direction for mission-critical capabilities — including usage-based billing, payment processing, customer-facing analytics, and product entitlements — while raising the bar for the engineers around you.

This role is ideal for a seasoned engineer who can operate at multiple altitudes: driving system design and long-term architecture decisions while staying hands-on in code. You'll be the connective tissue between engineering, product, finance, and go-to-market — translating complex business requirements into durable, scalable backend primitives that directly impact revenue and customer experience. You'll be expected to define not just what we build, but how we build it well.

Requirements

• 8+ years of experience building large-scale, fault-tolerant API-driven services and backend systems
• Demonstrated track record of tech lead or staff-level scope — owning system architecture decisions, influencing team direction, and delivering multi-quarter initiatives
• Deep expertise in designing relational database schemas and backend APIs that support complex product and business requirements at scale
• Strong experience leading and influencing cross-functional teams — comfortable partnering with product, finance, and non-technical stakeholders
• Expert-level proficiency in one or more of Golang, TypeScript, Python, C++, or Java
• Deep knowledge of distributed systems tradeoffs: consistency, availability, fault tolerance, and performance at scale
• Strong understanding of low-level systems concepts: multi-threading, memory management, networking, storage, and I/O
• Experience with infrastructure as code (Terraform, AWS CDK, Pulumi) and mature CI/CD workflows
• Experience with payment processors (e.g. Stripe) and billing systems strongly preferred
• Experience with Kubernetes and containerized deployments a plus
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent practical experience

Responsibilities

• Define and own the technical roadmap for Together's monetization and billing pipeline infrastructure, spanning usage metering, contract billing, entitlements, spend governance, and payments processing
• Lead architecture reviews for major systems investments, ensuring long-term scalability, correctness, and maintainability across the commerce stack
• Drive cross-functional alignment with Product, Finance, and Go-To-Market teams — translating business strategy into clear engineering requirements and system designs
• Mentor and grow engineers on the team through design feedback, code reviews, technical coaching, and setting high standards for craft
• Own data modeling and schema design for core commerce entities, making principled tradeoffs between flexibility, performance, and correctness
• Establish and evolve API contracts in collaboration with client engineering teams, enabling high-quality customer-facing product experiences
• Champion reliability and scalability — lead incident response, drive postmortems, and systematically improve the resilience of commerce APIs and distributed systems
• Identify and reduce technical debt proactively, balancing pragmatic delivery with sustainable engineering practices

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $230,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

Staff Engineer, Customer Insights

About the role

Together AI is seeking an experienced Staff Engineer to help found, build, and scale Customer Insights, the team responsible for the customer-facing visibility layer of Together’s Cloud. This role will shape how customers understand their activity, investigate what happened, respond when something needs attention, and govern their AI workloads with confidence.

In the near term, you will turn today’s fragmented visibility patterns into coherent product and platform foundations: historical analytics, activity history, audit logs, event timelines, notifications, and investigation workflows. You will partner closely with Together’s cloud product engineering teams and data platform team to make high-quality customer visibility a built-in capability across Together Cloud rather than a bespoke effort for each surface. Longer term, you will shape how these foundations evolve beyond dashboards and static views into AI-first investigation and insight workflows: systems that can summarize activity, explain anomalies, correlate events across surfaces, recommend actions, and provide trustworthy context to both human operators and autonomous agents.

This is a deeply hands-on role for an engineer who enjoys critical-path product and platform work. You will design the event, query, delivery, and governance systems behind customer insights while also building the user-facing workflows that help enterprise customers answer: what happened, who acted, when it happened, what matters now, and whether they need to act.

Responsibilities

• Design and drive the architecture for Together's Customer Insights platform, including customer-visible events, activity history, audit logs, timelines, notifications, and historical analytics and dashboards views.
• Build and operate the shared event and historical analytics visibility layer that helps product teams define important customer-facing events once and surface them consistently across analytics, logs, timelines, notifications, and governance views.
• Write and maintain critical-path backend and product code used by multiple teams and customer-facing surfaces.
• Partner with Data Platform and Observability engineering teams to leverage Together’s core data stack and capabilities to build out Customers Insights data collection and processing systems.
• Create customer workflows that connect summaries, timelines, evidence, actors, related objects, and next steps so users can investigate operational questions without relying on support or ad hoc analysis.
• Establish standards and review patterns for which events, evidence trails, notification hooks, and governance signals must exist before new product capabilities launch.
• Define reliability, freshness, completeness, and correctness measures for customer-facing visibility systems, then build the checks and operating loops needed to maintain trust at scale.
• Mentor engineers, influence architectural direction across teams, and help define the hiring bar as the Customer Insights area grows.
•  

Requirements

• 8+ years of experience building and operating large-scale distributed systems, product platforms, or customer-facing backend systems in production environments.
• Proven experience designing platforms or product systems used by multiple engineering teams or enterprise customers.
• Strong backend engineering skills in one or more of TypeScript, Go, Python, Java, C++, or similar production languages.
• Deep experience with event-driven systems, audit trails, activity feeds, analytics platforms, observability systems, notification systems, or investigation workflows.
• Strong data modeling and systems design judgment, including schemas, retention, indexing, query performance, access control, and correctness tradeoffs.
• Demonstrated ability to turn ambiguous customer and operational needs into clear technical architecture, incremental delivery plans, and durable product foundations.
• Experience partnering across product, infrastructure, data, security, and customer-facing teams to land cross-cutting architecture without relying on formal authority.
• Comfort writing critical production code while also setting technical direction, mentoring senior engineers, and raising engineering standards.
• Bachelor's or Master's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience building enterprise SaaS audit logs, governance tooling, compliance evidence systems, data lineage, or incident investigation products.
• Experience with high-volume event pipelines, streaming systems, OLAP or time-series storage, search systems, or large-scale analytical query engines.
• Experience building notification, alert routing, escalation, or workflow automation systems.
• Experience designing customer-facing analytics, reporting, dashboards, or operational intelligence products.
• Experience with multi-tenant cloud platforms, identity-aware access patterns, sensitive data handling, and retention controls.
• Experience with AI infrastructure, developer platforms, observability, or systems that support mission-critical enterprise workloads.
• Experience running production workloads on Kubernetes or cloud infrastructure and using Infrastructure as Code and modern CI/CD workflows.
• Experience building product surfaces in addition to backend platforms, especially where UX quality and technical correctness both matter.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200k-270k+ equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

About the Role

Together AI is seeking a highly experienced Staff Engineer to join the Product Engineering team, to own and evolve the Product UI Platform — the architectural foundation that powers how product teams build full-stack features across our web surface.This role is responsible for evolving the product runtime from its current monolithic growth architecture to a scalable, modular, and high-leverage platform that supports increasing scale, reliability requirements, and a growing number of feature engineers. You will define and drive the technical direction of the Next.js/typescript/nodejs web runtime, BFF layer, and application integration patterns, partnering peer-to-peer with Backend and API Platform leaders to ensure cohesive architectural evolution across layers. This is a deeply hands-on role for and experienced engineer with real life experience leading and implementing architectural evolution and is ready to take full ownership of a critical technical domain.

Responsibilities

• Lead the next phase of architectural evolution for the product application platform
• Design and implement foundational platform primitives used across product teams
• Reduce architectural entropy and duplication across the web surface
• Improve application-level performance and reliability metrics
• Drive incremental modularization without disrupting feature velocity
• Establish performance budgets and enforce application-layer guardrails
• Partner with Backend Platform to shape API ergonomics and integration boundaries
• Collaborate with SRE to ensure runtime stability and production readiness
• Write and maintain critical-path platform code
• Establish durable standards for how full-stack features are built
• Mentor engineers and help scale the platform capability over time

Requirements

• 8+ years building production-grade web applications and backend systems
• Demonstrated ownership of a product application platform used by multiple teams
• Deep expertise in React/Next.js/TypeScript and server-side application architecture
• Strong backend experience with TypeScript
• Experience evolving monolith architectures into modular systems
• Web Vitals performance optimization experience across browser → API → data layers
• Proven ability to drive and implement architectural change in a cross functional collaborative environment
• Experience establishing technical standards and scaling developer velocity
• History of owning complex technical decisions and their outcomes

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.

We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.

This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.

• Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
• Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.
• Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.
• Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.
• Join a small, early-stage team with outsized impact on a fast-growing product area.

Responsibilities

• Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.
• Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.
• Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.
• Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.
• Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.
• Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.
• Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.
• Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.
• Lay the groundwork for multiple new products down the line.

Requirements

• 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.
• Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.
• Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).
• Track record of shipping ML systems to production with measurable performance improvements.
• Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.
• Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.
• Experience training or fine-tuning speech models is a plus.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As a Senior Network Engineer at Together, you are responsible for designing, implementing, and maintaining our network infrastructure to ensure seamless connectivity and optimal performance for all user-facing services and production systems. As both a strategic planner and a hands-on engineer, you apply sound networking principles, operational discipline, and advanced automation to our network environments.

You specialize in networking systems—including routing, switching, network security, and protocols—implementing best practices for availability, reliability, and scalability. You have a keen interest in network design, optimization, and emerging technologies in HPC-based data center networking.

Outstanding problem-solving abilities and a comprehensive understanding of fundamental network theory are also critical to your success.

Requirements

• 8+ years of professional experience building, managing, and supporting large-scale hybrid data center networks (excluding enterprise networks).
• High level of proficiency with TCP/IP networking architecture and technologies such as BGP, OSPF, VXLAN, EVPN, and QoS.
• Experience developing network automation pipelines using Python, Ansible, or other languages/tools utilized in infrastructure automation.
• Proficient in using tools such as Wireshark, tcpdump, nmap, MTR, and curl to identify connectivity issues, latency problems, and network bottlenecks.
• Experience designing and supporting multi-tenant networks
• Hands-on experience deploying and supporting network devices from Cisco, Arista, Juniper, and Mellanox.
• Experience working with cloud networks such as AWS, GCP, and Azure.
• Solid experience working in and troubleshooting within a Linux environment.

Responsibilities

• Design, deploy, manage and maintain global multi-vendor, multi-protocol high performance compute networks.
• Analyze data to diagnose and identify root causes to network issues to minimize downtime
• Evaluate and recommend network technologies, hardware, and software solutions.

• Participate in design reviews to ensure the proposed network architecture aligns with business needs and is optimized for performance, scalability, and reliability. 
• Manage relationships with external vendors and partners to test and verify hardware and software selections.

• Develop, and deploy systems and tools to keep all networks running reliably and efficiently
• Establish and implement industry best practices and contribute to the design of new scalable network solutions
• Ensure compliance with IT governance standards and best practices.
• Lead projects to address complex technical challenges, directly contributing to roadmaps and partner alongside the best engineers in the industry to develop world-class solutions

Preferred

• Knowledge of RoCE and Infiniband protocols a plus
• Experience with Docker, Kubernetes, or Slurm a plus 
• Understanding of AI training workloads and the demands they exert on networks a plus

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

This is the first dedicated data hire on Together AI's Finance team. You will own the data layer that Finance runs on — building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales.

A significant portion of your work will touch the data behind the economics of Together's infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together's Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets — aligning on data contracts, representing Finance's requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted.

Responsibilities

• Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics
• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably
• Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics
• Partner with Strategic Finance, FP&A, and Accounting teams on the data infrastructure behind forecasting, cost modeling, and other financial analyses
• Set data quality standards across Finance data products and own incident response when Finance-critical pipelines break
• Build the data foundation – clean, well-structured, documented, and reliably maintained – that enables Finance team to self-serve data analysis and supports AI automation and agentic workflows 

Requirements

• 5+ years in an analytics engineering or data engineering role, with meaningful time supporting Finance or business operations teams
• Expert SQL and production-grade dbt experience — models, tests, docs, snapshots, incremental strategies; you've designed a dbt project from scratch and maintained it
• Hands-on experience with Snowflake and Airflow in production; familiarity with Astronomer and the Cosmos dbt integration is a strong plus
• Solid dimensional modeling fundamentals: star schemas, slowly changing dimensions, fact table grain — you can apply Kimball principles without needing to look them up
• Strong dashboarding skills with a track record of executive-facing reporting that people actually use; experience with Hex or a comparable notebook/BI tool
• Clear communicator who can align stakeholders on metric definitions and translate between engineering tradeoffs and Finance requirements in both directions
• High comfort with ambiguity; this role will require scoping problems from scratch, not executing against pre-defined specs

Nice to Have

• Experience with financial data or billing data such as ARR, usage-based billing, invoice reconciliation, revenue recognition patterns, etc.. We operate a usage-based billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200k -$240k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy.  

About the Role

Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale.

If you get a thrill from optimizing latency down to the last millisecond, this is your playground. You’ll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory.

You’ll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency.

• Shape the core inference backbone that powers Together AI’s frontier models.
• Solve performance-critical challenges in global request routing, load balancing, and large-scale resource allocation.
• Work with state-of-the-art accelerators (H100s, H200s, GB200s) at global scale.
• Partner with world-class researchers to bring new model architectures into production.
• Collaborate with and contribute to the open source community, shaping the tools that advance the industry.
• A culture of deep technical ownership and high impact — where your work makes models faster, cheaper, and more accessible.
• Competitive compensation, equity, and benefits.

Responsibilities 

• Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods.
• Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers.
• Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling — including smart rate limiting and regulation — to ensure fairness and consistent experience across all users.
• Engineer trade-offs between latency and throughput to serve diverse workloads efficiently.
• Optimize prefix caching to reduce model compute and speed up responses.
• Collaborate with ML researchers to bring new model architectures into production at scale.
• Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations.

Requirements

• 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices.
• Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems.
• Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance.
• Expert-level programming in one or more of: Rust, Go, Python, or TypeScript.
• Knowledge of modern LLMs and generative models and how they are served in production is a plus.
• Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy.
• Experience with Kubernetes or container orchestration is a strong plus.
• Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy