Senior Software Engineer, Energy Storage

This position is on a team building the software platform that powers optimized control and market participation of battery energy storage systems (BESS) — software that runs both on site controllers and in the cloud. Our scope spans the full stack: compute infrastructure, telemetry, asset modeling, alerting, feature ingestion and storage for forecasting and optimization, simulation and operational control orchestration, and integration with energy markets. We're a lean team that holds ourselves to high standards in both the quality of what we build and the speed at which we build it. We value collaboration, trust, learning, and engineering excellence, and we genuinely enjoy building great things together.

Responsibilities will include:

• Contribute to BESS data engineering — building and maintaining telemetry pipelines and stores, and feature ingestion and storage systems for forecasting and optimization
• Design, build, and maintain simulation and training infrastructure — platforms for running and orchestrating simulations at scale
• Develop and operate real-time forecast and optimization workflows, orchestrating pipelines that drive BESS operations
• Support energy market integration, including data ingestion and bid management
• Collaborate across the full stack and across team boundaries to ensure the product system works well as a whole
• Write well-tested, well-monitored software and iteratively improve it over time
• Apply AI tools to accelerate development while maintaining high system design quality and code standards

Desired Qualifications: 

• Strong software design instincts — thinks in systems, reasons from first principles, and understands the real-world challenges of building available, reliable, scalable, and secure distributed systems
• Comfortable using AI tools to move faster without letting them erode system design or code quality
• Excellent collaborator — communicates clearly, listens well, and makes the people around them better
• Bias toward action — takes initiative, makes progress in ambiguous situations, and doesn't wait for perfect information
• Systems thinker and owner — willing to think and collaborate across team boundaries to make sure the product works well as a whole
• Rigorous about quality — writes well-tested, well-monitored software and iterates on it over time
• B.S. or advanced degree in Software Engineering, Computer Science, or another discipline, combined with 2-5 years of experience in software engineering.
• Experience with relevant technologies a plus: Kubernetes, Rust, Python, NATS, PostgreSQL/TimescaleDB, SQLite
• 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

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  

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

About the role

We are seeking a Staff Software Engineer to build and operate the safety, oversight, and intervention mechanisms that protect Claude on third-party cloud service provider (CSP) platforms. As the engineer responsible for Safeguards on those surfaces, you will ensure that every request served through our CSP partners is monitored for misuse, enforced against policy, and compliant with the data residency and privacy commitments that enterprise CSP customers expect.

You will sit at the seam between the Safeguards organization and the Cloud Inference team: taking classifiers, detection signals, and enforcement policies developed by Safeguards and making them run reliably inside a CSP partner’s infrastructure at serving-path latency and scale. You will own the architecture that lets our safeguards operate within those constraints without gaps. You will build, deploy and operate the multi-layered defenses that catch unwanted model behavior in real time, the telemetry pipelines that give us situational awareness over CSP traffic, and the enforcement hooks that let us act quickly when something goes wrong. Your work will directly determine whether Anthropic can ship frontier models on CSP platforms at the same safety bar we hold ourselves to on our first-party API.

Responsibilities:

• Build, deploy and operate real-time safeguards infrastructure—classifiers, rate limits, enforcement actions, and intervention hooks—embedded directly in the third-party CSP inference serving path
• Design and maintain the data residency and privacy architecture for safeguards signals on CSP platforms, ensuring we can detect abuse and monitor model behavior while honoring regionalization boundaries and enterprise contractual commitments
• Develop telemetry, logging, and evaluation pipelines that give Safeguards, Policy, and T&S operational teams situational awareness over CSP traffic and close the visibility gap between third-party and first-party serving
• Dive into the CSP serving stack to identify the lowest-impact points to gather signals or introduce interventions without degrading latency, stability, or overall architecture
• Hold a high operational bar: own on-call, drive root-cause analyses and postmortems for safeguards incidents on CSP platforms, and build systems that reduce the human intervention required to keep Claude safe
• Work closely with Safeguards research, Policy & Enforcement, the Cloud Inference team, and CSP partner contacts to turn detection research and policy decisions into production enforcement that works inside a partner’s cloud.

You may be a good fit if you:

• Have a Bachelor’s degree in Computer Science, Software Engineering, or comparable experience
• Have 7+ years of experience in high-scale, high-reliability software development, ideally with exposure to trust & safety, anti-abuse, fraud, or integrity systems
• Are proficient in Python and comfortable working across the stack—from request-path services to data pipelines to internal tooling
• Think adversarially: you can see a system from a bad actor’s perspective, anticipate how they will respond to countermeasures, and design defenses in depth rather than single points of enforcement
• Have experience scaling infrastructure to accommodate rapid traffic growth while keeping latency and reliability within tight budgets
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Have strong communication skills and can explain complex technical and risk tradeoffs to non-technical stakeholders across Policy, Legal, and partner organizations
• Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space

Strong candidates may also have experience with:

• Building trust and safety, anti-spam, fraud, or abuse detection and mitigation mechanisms for AI/ML systems, or the infrastructure to support these systems at scale
• Machine learning serving infrastructure (GPUs/TPUs, inference servers, load balancing) and the operational realities of running models in production
• Major cloud platform internals—IAM, Network/service perimeter controls, regional resource constraints, cloud-native logging/monitoring—or experience shipping software that runs inside a partner’s cloud rather than your own
• Data residency, privacy engineering, or compliance-constrained architectures, particularly where telemetry has to stay within regional or contractual boundaries
• Working closely with operational and human-review teams to build custom internal tooling, admin UX, and alerting
• Adversarial mindset: has shipped defenses against motivated attackers before, knows what it feels like when they adapt, and can sprint to close a gap before it becomes an incident
• Comfortable operating at the intersection of platform/infra engineering and trust & safety—neither a pure infra engineer nor a pure T&S engineer, but someone who can credibly do both
• Has shipped software that runs inside someone else’s infrastructure (partner cloud, embedded deployment, or similar) and knows how to get things done when you don’t control the whole stack
• Senior enough to own a cross-team seam independently, drive consensus across orgs, and make latency/safety tradeoff calls without escalation
• TypeScript or Rust, and agentic coding tools such as Claude Code

Location: This position can work onsite or hybrid from San Francisco Bay Area. 
Travel: Up to 15%, domestic or international.
Job ID: 1558

The Role: 

We are looking for a Senior Staff Software Architect to lead the design and evolution of our next-generation Network Monitoring Platform. You’ll be part of a cross-functional team whose mission is to lead IonQ on its journey to build the world’s best quantum computers to solve the world’s most complex problems.

In this role, you will own the end-to-end architecture of a high-scale, data-intensive network monitoring platform — from data modeling and ingestion pipelines to cloud-native deployment. You are a hands-on technical leader who writes production code, drives critical architectural decisions, and has deep experience building systems that monitor large fleets of devices at scale. The ideal candidate brings strong Go and/or Rust expertise and thrives at the intersection of systems engineering and distributed data platforms.

Responsibilities:

• Architect cloud-native ingestion and processing pipelines capable of handling telemetry from hundreds of thousands of devices, leveraging streaming platforms and time-series storage at scale.
• Define and own the platform’s unified YANG-based data model, spanning device configuration state, operational telemetry, and topology relationships across heterogeneous network environments, serving as the authoritative schema from which ingestion pipelines, storage structures, and API contracts are derived.
• Write and review production-quality code in Go and/or Rust for performance-critical platform components including collectors, aggregators, and real-time processing engines.
• Define and enforce data partitioning, sharding, and retention strategies to sustain high-volume device event streams while meeting latency and durability requirements.
• Lead the design of cloud-native deployment patterns (Kubernetes, service mesh, autoscaling) to ensure the platform operates reliably at global scale across multi-cloud environments.
• Evaluate and drive adoption of purpose-fit technologies — time-series databases, graph stores, stream processors — with a focus on operational scalability and long-term maintainability.
• Partner with Product and Engineering to translate monitoring requirements into platform capabilities, ensuring architectural decisions are reflected in roadmap milestones and engineering specifications.
• Mentor senior engineers through architecture reviews, coding standards, and hands-on technical guidance, raising the bar for platform quality and engineering practices.

Requirements:

• 12+ years of experience in software or platform architecture, with at least 5 years leading architecture for large-scale, data-intensive distributed systems.
• Substantial experience building and operating device monitoring systems at scale — with direct exposure to telemetry ingestion pipelines, fleet management, and real-time alerting across large device populations.
• Proven hands-on coding ability; production experience with Go and/or Rust is strongly preferred for this role.
• Deep expertise in data modeling for high-volume systems, including schema design, time-series storage (InfluxDB/Timescale), event streaming (Kafka/Kinesis), and graph data models for network topology.
• Solid understanding of cloud-native application design — including containerization, Kubernetes orchestration, microservices, and cloud infrastructure across AWS, GCP, or Azure.

Preferred Qualifications:

• Proficiency in both Go and Rust, with a track record of shipping production services in at least one of these languages.
• Background in network management platforms or network equipment vendors (e.g., Juniper, Cisco, Nokia), with familiarity with telemetry protocols such as gNMI, NETCONF, or SNMP.
• Experience designing multi-tenant SaaS platforms where data isolation, schema evolution, and scalability across customer tiers are first-class concerns.
• Contributions to open-source infrastructure or observability projects, or published technical writing on distributed systems and data engineering topics.
• Familiarity with techniques relevant to high-throughput data collection.

The approximate base salary range for this position is $216,136 - $282,978. The total compensation package includes base, bonus, equity, and a range of benefit options found on our career site.

About World Labs:

We build foundational world models that can perceive, generate, reason, and interact with the 3D world — unlocking AI's full potential through spatial intelligence by transforming seeing into doing, perceiving into reasoning, and imagining into creating. 

We believe spatial intelligence will unlock new forms of storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical worlds.

We bring together a world-class team, united by a shared curiosity, passion, and deep backgrounds in technology — from AI research to systems engineering to product design — creating a tight feedback loop between our cutting-edge research and products that empower our users.

Role Overview

We are looking for a Platform Engineer to own Developer Infrastructure at World Labs.

This is a high impact systems role focused on build systems, testing infrastructure, and release and rollout pipelines, the critical path that determines how code moves from local development to production.

You will define and operate the systems that make our engineering organization fast, reliable, and scalable, in an environment where both the codebase and workloads are evolving quickly.

You will be responsible for the architecture and operation of the systems that power developer velocity and production safety, making foundational decisions around build performance, dependency structure, test execution, and release reliability.

This role is about turning complex, failure prone workflows into systems that are fast, correct, and reproducible, and setting the technical direction for how we build and ship software.

This is a hands on role. You will design, build, and operate these systems directly.

What You Will Do:

• Own the design and evolution of the build, test, and release systems that power the platform.
• Define architecture for a Bazel based monorepo, including performance, caching, and dependency graph scalability.
• Improve build performance and correctness, including incremental builds, caching strategies, and graph optimization.
• Design and operate test infrastructure, focusing on reliability, isolation, and signal quality.
• Build and improve release and rollout systems, including deployment pipelines, canarying, and rollback.
• Improve end to end developer velocity, from local iteration to production deployment.
• Debug and resolve complex issues across the pipeline, including build failures, dependency issues, test flakiness, and release regressions.
• Establish standards for reproducibility, observability, and operability across build and release systems.
• Identify and eliminate systemic failure modes across the development lifecycle.
• Contribute broadly across infrastructure and reliability work when needed.
• Mentor engineers and raise the bar for system design and technical decision making.

Key Qualifications:

• 5-10 years of experience building and operating production systems at scale, with ownership of critical infrastructure.
• Strong experience with build systems and dependency graphs such as Bazel, Buck, Pants, or similar, or the ability to quickly ramp on Bazel in a large monorepo environment.
• Experience designing and improving build, test, and release pipelines, with a focus on performance, correctness, and reproducibility.
• Strong systems understanding of how code moves from source to build to test to production.
• Hands on experience debugging complex system issues, including build failures, dependency issues, test flakiness, and release regressions.
• Experience owning systems with strict reliability and performance requirements.
• Strong proficiency in at least one of Python, Go, or Rust, with a strong preference for Python
• Comfort working across languages in a polyglot codebase.
• Proven ability to define architecture and drive technical decisions end to end.
• Strong judgment in balancing developer velocity, system complexity, and reliability.
• Ability to operate effectively in ambiguous, fast moving environments with high ownership.
• You have worked on systems where build performance, correctness, and reproducibility were first order concerns, not afterthoughts.
  
  

Preferred Qualifications:

• Deep experience with Bazel at scale, including remote caching, remote execution, and build graph optimization.
• Experience designing hermetic and reproducible build systems.
• Experience improving test infrastructure at scale, including eliminating flakiness and improving signal quality.
• Experience building or operating release and rollout systems, including canarying, staged rollouts, and rollback mechanisms.
• Experience instrumenting systems for observability and debugging of build, test, and release pipelines.
• Experience in early stage or high growth environments.

Who You Are:

• Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.
• Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.
• Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people.
• Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence.

We're hiring the brightest minds from around the globe to bring diverse perspectives to our cutting-edge work. If you're ready to work on technology that will reshape how machines perceive and interact with the world, World Labs is your launchpad.

Join us, and let's make history together.

Equal Opportunity & Pay Transparency

Equal Employment Opportunity

World Labs is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected under applicable law. We welcome all qualified applicants and are committed to providing reasonable accommodations throughout the hiring process upon request.

California Pay Transparency

In accordance with California law, we disclose the following:

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

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• 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 modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

Scale's Physical AI business unit is dedicated to solving the data bottleneck across Robotics, Autonomous Vehicles, and Computer Vision. This position will be a key contributor in conducting applied research in Physical AI and developing ML pipelines for processing, training, and fine-tuning on data collected by Scale, with a specific focus on optimizing algorithms and pipelines to run efficiently on GPUs in the cloud. In this role, you will have the opportunity to advance research, shape Scale’s offerings, and expand the frontier of data and model evaluation for Physical AI.

The Role 

As an ML Systems Engineer on the Physical AI team, you will design and build platforms for scalable, reliable, and efficient serving of foundation models specifically tailored for physical agents. Our platform powers cutting-edge research and production systems, supporting both internal research discovery and external customer use cases for autonomous vehicles and robotics.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging the gap between Physical AI research and production engineering to accelerate innovation across the company.

You Will: 

• Build & Scale: Maintain fault-tolerant, high-performance systems for serving robotics-related models and foundation models at scale, ensuring low latency for real-time applications.
• Platform Development: Build an internal platform to empower model capability discovery, enabling faster iteration cycles for research teams working on robotics.
• Collaborate: Work closely with Robotics researchers and Computer Vision engineers to integrate and optimize models for production and research environments.
• Design Excellence: Conduct architecture and design reviews to uphold best practices in system scalability, reliability, and security.
• Observability: Develop monitoring and observability solutions to ensure system health and real-time performance tracking of model inference.
• Lead: Own projects end-to-end, from requirements gathering to implementation, in a fast-paced, cross-functional environment.

Ideally, You’d Have: 

• Experience: 4+ years of experience building large-scale, high-performance backend systems, with deep experience in machine learning infrastructure.
• Algorithm Optimization: Deep experience optimizing computer vision and other machine learning algorithms for cloud environments, including GPU-level algorithm optimizations (e.g., CUDA, kernel tuning).
• Programming: Strong skills in one or more systems-level languages (e.g., Python, Go, Rust, C++).
• Systems Fundamentals: Deep understanding of serving and routing fundamentals (e.g., rate limiting, load balancing, compute budgets, concurrency) for data-intensive applications.
• Infrastructure: Experience with containers (Docker), orchestration (Kubernetes), and cloud providers (AWS/GCP).
• IaC: Familiarity with infrastructure as code (e.g., Terraform).
• Mindset: Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves: 

• Exposure to Vision-Language-Action (VLA) models.
• Knowledge of high-performance video processing (e.g., FFmpeg, NVDEC/NVENC) or 3D data handling (point clouds).
• Familiarity with robotics middleware (e.g., ROS/ROS2) or AV data formats.

About the Team

This role will lead either our Gateway or Agent team, depending on your experience and interests.

Both teams sit on the critical path of every ngrok connection and are central to our reliability, performance, and customer trust.

• Gateway Team: Owns the core infrastructure that handles and shapes all traffic flowing through ngrok—routing, security enforcement, rate limiting, and observability. Every request passes through this layer, and its correctness and performance are foundational to everything we do.
• Agent Team: Builds the software that runs on the customer side of every connection. The Agent is what developers install and trust to securely expose their systems to the internet, and it must perform reliably across unpredictable, real-world environments.

What You’ll Actually Do

Lead a team that ships and learns quickly

You’ll manage and coach a team of 5–7 engineers. The goal isn’t just shipping—it’s building a team that can consistently make good decisions, move fast, and improve over time.

Treat management like a systems problem (with humans in the loop)

You’ll design how your team works: planning, execution, retros, feedback loops, and decision-making. You’ll tune the system, not just react to it.

Stay close enough to the code to matter

You won’t be coding every day, but you’ll get into the details when needed—reviewing designs, debugging tricky issues, and helping the team make better technical tradeoffs.

Drive product and technical direction together

This isn’t “just execution.” You’ll help shape what the team builds—balancing product work, technical investments, and experiments that actually teach you something.

Build a team people want to be on

You’ll coach junior and senior engineers, create psychological safety, and raise the bar on both performance and collaboration.

Connect the team to the bigger picture

You’ll make sure your team understands how their work ties to ngrok’s product, customers, and business. Context isn’t optional here. You’ll work closely with senior leadership and functional orgs to shape and meaningfully impact company culture and roadmap.

You Might Be a Great Fit If…

• You’ve spent 5+ years as a software engineer and comfortable in Go, Rust, Java, or C/C++
• You have 4+ years of engineering leadership experience
• You think in systems—whether that’s distributed systems or team dynamics
• You’re comfortable zooming in (code, debugging) and zooming out (strategy, org design)
• You’ve built things from scratch—teams, processes, or products
• You communicate clearly, directly, and without unnecessary fluff

Bonus points if you’ve:

• Contributed to open source, blogs, or conferences
• Worked in developer tools or product-led growth environments
• Built teams in ambiguous, early-stage contexts

Tech Stack

ngrok runs entirely on AWS. Engineers develop by using remote development tools and/or ssh to connect to remote EC2 environments that run a full Kubernetes cluster of the ngrok stack, closely mirroring production. The codebase is primarily Go and TypeScript. We use Postgres for persistence, Kafka for streaming, Protobuf for service boundaries, and Kubernetes, Terraform, Helm, and Buildkite to operate and ship reliably. React is used for user interfaces, and GitHub supports our development workflows and remembers everything.

Location

This is a remote position for candidates outside of the Bay Area and a hybrid role for candidates within commuting distance to San Francisco. Our Bay Area employees commute to the office on Tuesdays and Wednesdays.

Sponsorship

All candidates must be US-based, and legally authorized to work in the United States.

At this time, ngrok is unable to provide visa sponsorship for this position. Applicants must be authorized to work in the United States on a permanent, ongoing basis without the need for current or future sponsorship.

Compensation

Engineering Manager: $225,000 – $275,000

Job level and actual compensation will be evaluated based on factors including, but not limited to, qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), internal equity with other team members, market data, and specific work location. We provide an attractive mix of salary and equity.

#LI-Remote

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.

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure.

The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards.

This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours.

Responsibilities:

• Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP
• Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour
• Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.)
• Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code
• Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership
• Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services

Qualifications:

You might be a great fit if you match some of the following:

• 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work
• Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes
• A deep understanding of Linux and networking concepts, including low-level fundamentals, and how they work together in complex systems
• Experience building security-related features or platforms such as runtime monitoring, CSPM, or vulnerability management
• Experience with a cloud provider (AWS, GCP, or Azure) and their security best practices and building blocks
• Hands-on experience with Kubernetes and its security ecosystem (e.g. RBAC, OPA/Gatekeeper, Kyverno, eBPF, Falco, Tetragon)
• A systems mindset: you think about failure modes, performance, observability, and operability alongside security and correctness
• Strong communication skills and the ability to explain complex security concepts and tradeoffs to both technical and non-technical stakeholders

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 2263171228

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

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 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  

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

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

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

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

Sigma is transforming how businesses run by delivering a high performance platform on the modern data architecture. Hence, we are growing the engineering team and looking for engineers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible for all users.

What You Will Be Doing

• Build testing infrastructure and tooling, including: AI test generation, test harnesses, API, hermetic test environments, load and performance frameworks
• Enable testability of systems and services.
• Build with modern tools and languages, including K6, Rust, and Go
• Refine best practices around making our systems and services high quality
• Participate in test planning and quality strategy reviews
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be delivering code a majority of their time

Qualifications We Need

• Strong Computer Science fundamentals
• 5+ years industry experience building and maintaining high-quality testing software, especially software other engineers use
• Strong understanding of Testing and Quality Engineering principles
• You drive Quality Culture and feel accomplished enabling others
• Desire to be a great teammate and have fun at work
• Strong sense of craftsmanship, and a healthy academic curiosity

Qualifications We Want (also, skills you’ll learn!)

• Experience with back-end testing frameworks
• AI Test Generation
• Integration, API, and contract testing
• CI/CD Testing Proficiency
• Multi-cloud experience (GCP, AWS, Azure)
• Startup experience

Additional Job details

The base salary range for this position is $170k - $240k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.

About the role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world.

Key responsibilities

• Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning
• Partner across teams to ensure new compute capacity is ingested on time
• Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity
• Collaborate with security owners to ensure clusters are provisioned secure-by-default
• Define and drive strategy on cluster scalability, homogeneity and fault tolerance
• Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health
• Support the growth of engineers around you through technical mentorship and coaching

Minimum qualifications

• Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
• Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
• Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems
• Ability to build alignment across senior stakeholders and communicate effectively at all levels

Preferred qualifications

• 8+ years of software engineering experience, including time as a technical lead setting direction for a team
• Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes)
• Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like)
• Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield)
• Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS)
• Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance
• Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows)
• Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems

The Role

Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. 

The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: 

1. Environments for Software Engineering / coding agents 
2. UI-Environments for Computer-Use/Browser-Use agents 
3. MCP-based Environments for general function-calling agents across various enterprise and consumer applications

The Staff Research Engineer – Code will own end-to-end the creation of datasets, RL environments, and evals for frontier AI labs in the domain of coding agents and software engineering. This is a hands-on technical leadership role where you influence revenue directly – you will be mapped to one or more AI labs and interface directly with researchers / engineers at those labs to understand their needs and build data offerings to address those needs. To achieve this, you will build and manage teams of software engineers, researchers, QAs, and contractors/data-annotators from Turing’s talent pool of 4M+ developers.  

You’ll be responsible for delivering projects at frontier quality and scale—owning data quality, throughput, and timely delivery. You’ll define and manage data pipelines, validation workflows, and review processes to ensure datasets meet the highest standards for realism, correctness, and diversity. You’ll also develop automations, synthetic data generation systems, and internal tools to scale production efficiently. 

In short, you’ll run your project like a startup within Turing, owning both the technical architecture and the operational execution required to produce best-in-class datasets/environments/evals to make the world’s best coding agents and models even better at real-world coding tasks across the software development lifecycle.

What you’ll do

1. End-to-End Ownership: Data Quality, Process Design, and Team Building

• Lead the creation of datasets, rl environments, and evals focused on Coding Agents / Software Engineering for one or more AI lab customers.
• Ensure that everything you ship to clients meets frontier standards for realism, correctness, diversity, and difficulty.
• Set up quality rubrics, automated validation scripts, and human review processes for every stage of data generation.
• Build and lead cross-functional teams of software engineers, researchers, QAs, and data creators drawn from Turing’s 4M+ developer network.
• Interview, onboard, train, and mentor team members to ensure consistent output quality and technical excellence.

2. Collaborate with Researchers at Frontier Labs

• Act as the primary technical point of contact for your customer projects, interfacing directly with researchers and engineers at frontier AI labs to understand their coding agent roadmap and model data needs, to gather feedback, and to co-define success criteria for your projects.
• Provide regular progress updates, surface insights from model evaluations, and incorporate client feedback to improve future iterations.

3. Drive Research, Sales Enablement, and Industry Thought Leadership

• Fine-tune models in-house on Turing-generated datasets or Turing-rl-environment generated trajectories to determine model improvement as a proof of data quality
• Proactively build benchmarks and run evals on frontier models and coding agents to identify strengths and weaknesses on SWE tasks, and leverage these insights to inform product roadmap
• Equip customer-facing teams with the Evaluation reports, sample datasets, and trainings to enable them to communicate your data offerings to customers most effectively
• Publish research papers and technical posts on Turing’s data products, innovations in our synthetic data generation / automation pipelines, evaluations of frontier agents and models, and Turing’s model fine-tuning results on our datasets.

4. Build Tools and Infrastructure

• Oversee development of internal tools that accelerate data generation and verification (e.g., automated data scraping pipelines, unit test generators, repo sandboxing).
• Design dashboards and APIs for customers to run model evals, view performance reports, and integrate Turing data directly into their post-training pipelines.

What we’re looking for

• Post-training experience on SWE tasks or experience building coding agents: We expect that you have a deep understanding of data ingredients and design principles that lead to measurable coding model improvements, either from fine-tuning models to improve SWE capabilities or building your own coding agents to improve upon SWE capabilities of the base model.
• Engineering Management experience: have led teams of engineers in the past, including interviewing/hiring them and setting up QA processes.Hands-on technical capability: Fluency in Python and proficiency in one or more major languages (C++, Java, Go, Rust, or JS).
• Operational leadership: Proven ability to manage complex data pipelines, multi-stakeholder delivery, and concurrent high-stakes projects.
• Cross-functional communicator: ability to communicate clearly with researchers at frontier AI labs, subject matter experts for various domains, and diverse teams.
• Background in Computer Science, Machine Learning, or related technical field preferred.

Why Turing

• Work directly with the world’s leading AI labs and enterprises at the cutting edge of post-training and RL environment design.
• Real impact (path to AGI): your datasets and environments will directly influence the trajectory toward Artificial General Intelligence and, ultimately, Superintelligence. Coding is the core reasoning substrate of intelligence—advancing models’ ability to understand, design, and write code is effectively advancing their capacity for logic, planning, and abstract thought.
• Real Impact (GDP): automating software engineering unlocks one of the largest productivity frontiers in history. The software engineering market represents trillions in global GDP, and every percentage gain in automation translates to profound efficiency and innovation benefits across all industries.
• Talent-dense team, where you'll find high autonomy, rapid iteration, and an exceptional learning curve.

Compensation: $250,000 to $350,000 OTE + Equity

The Role

We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. 

The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: 

1. Environments for Software Engineering / coding agents 
2. UI-Environments for Computer-Use/Browser-Use agents 
3. MCP-based Environments for general function-calling agents across various enterprise and consumer applications

The Frontier Data Lead – Code will own end-to-end the creation of datasets, RL environments, and evals for frontier AI labs in the domain of coding agents and software engineering. This is a hands-on technical leadership role where you influence revenue directly – you will be mapped to one or more AI labs and interface directly with researchers / engineers at those labs to understand their needs and build data offerings to address those needs. To achieve this, you will build and manage teams of software engineers, researchers, QAs, and contractors/data-annotators from Turing’s talent pool of 4M+ developers.  

You’ll be responsible for delivering projects at frontier quality and scale—owning data quality, throughput, and timely delivery. You’ll define and manage data pipelines, validation workflows, and review processes to ensure datasets meet the highest standards for realism, correctness, and diversity. You’ll also develop automations, synthetic data generation systems, and internal tools to scale production efficiently. 

In short, you’ll run your project like a startup within Turing, owning both the technical architecture and the operational execution required to produce best-in-class datasets/environments/evals to make the world’s best coding agents and models even better at real-world coding tasks across the software development lifecycle.

What you’ll do

1. End-to-End Ownership: Data Quality, Process Design, and Team Building

• Lead the creation of datasets, rl environments, and evals focused on Coding Agents / Software Engineering for one or more AI lab customers.
• Ensure that everything you ship to clients meets frontier standards for realism, correctness, diversity, and difficulty.
• Set up quality rubrics, automated validation scripts, and human review processes for every stage of data generation.
• Build and lead cross-functional teams of software engineers, researchers, QAs, and data creators drawn from Turing’s 4M+ developer network.
• Interview, onboard, train, and mentor team members to ensure consistent output quality and technical excellence.

2. Collaborate with Researchers at Frontier Labs

• Act as the primary technical point of contact for your customer projects, interfacing directly with researchers and engineers at frontier AI labs to understand their coding agent roadmap and model data needs, to gather feedback, and to co-define success criteria for your projects.
• Provide regular progress updates, surface insights from model evaluations, and incorporate client feedback to improve future iterations.

3. Drive Research, Sales Enablement, and Industry Thought Leadership

• Fine-tune models in-house on Turing-generated datasets or Turing-rl-environment generated trajectories to determine model improvement as a proof of data quality
• Proactively build benchmarks and run evals on frontier models and coding agents to identify strengths and weaknesses on SWE tasks, and leverage these insights to inform product roadmap
• Equip customer-facing teams with the Evaluation reports, sample datasets, and trainings to enable them to communicate your data offerings to customers most effectively
• Publish research papers and technical posts on Turing’s data products, innovations in our synthetic data generation / automation pipelines, evaluations of frontier agents and models, and Turing’s model fine-tuning results on our datasets.

4. Build Tools and Infrastructure

• Oversee development of internal tools that accelerate data generation and verification (e.g., automated data scraping pipelines, unit test generators, repo sandboxing).
• Design dashboards and APIs for customers to run model evals, view performance reports, and integrate Turing data directly into their post-training pipelines.

What we’re looking for

• Post-training experience on SWE tasks or experience building coding agents: We expect that you have a deep understanding of data ingredients and design principles that lead to measurable coding model improvements, either from fine-tuning models to improve SWE capabilities or building your own coding agents to improve upon SWE capabilities of the base model.
• Engineering Management experience: have led teams of engineers in the past, including interviewing/hiring them and setting up QA processes.Hands-on technical capability: Fluency in Python and proficiency in one or more major languages (C++, Java, Go, Rust, or JS).
• Operational leadership: Proven ability to manage complex data pipelines, multi-stakeholder delivery, and concurrent high-stakes projects.
• Cross-functional communicator: ability to communicate clearly with researchers at frontier AI labs, subject matter experts for various domains, and diverse teams.
• Background in Computer Science, Machine Learning, or related technical field preferred.

Why Turing

• Work directly with the world’s leading AI labs and enterprises at the cutting edge of post-training and RL environment design.
• Real impact (path to AGI): your datasets and environments will directly influence the trajectory toward Artificial General Intelligence and, ultimately, Superintelligence. Coding is the core reasoning substrate of intelligence—advancing models’ ability to understand, design, and write code is effectively advancing their capacity for logic, planning, and abstract thought.
• Real Impact (GDP): automating software engineering unlocks one of the largest productivity frontiers in history. The software engineering market represents trillions in global GDP, and every percentage gain in automation translates to profound efficiency and innovation benefits across all industries.
• Talent-dense team, where you'll find high autonomy, rapid iteration, and an exceptional learning curve.

Compensation: $250,000 to $350,000 OTE + Equity

ABOUT THE ROLE

Zipline is looking for software engineers to build the tools and infrastructure that power our systems validation and flight test organizations. This team develops precise, efficient, and scalable software solutions used to validate aircraft and ground systems at every level.

Our work spans everything from integrating real avionics, sensors, actuators, and radios with high-fidelity simulated environments in bench-top Hardware-in-the-Loop (HIL) setups, to building applications that plan, orchestrate, and evaluate thousands of automated nominal and off-nominal real-world flight tests every day. This role directly impacts the speed, confidence, and quality of hardware and software development at Zipline.

In this role, you will develop a deep understanding of Zipline’s end-to-end logistics system and work closely with cross-functional partners who rely on your tools to deliver reliable, flight-ready software. Most importantly, the systems you build will serve as the final line of defense before software and hardware is deployed globally to perform critical, real-world deliveries.

WHAT YOU’LL DO

• Design, develop, and maintain HIL test infrastructure that integrates real aircraft hardware with simulated systems and environments.
• Develop software tools, frameworks, and services to enable large-scale automated and semi-automated system validation.
• Support a high-throughput flight test organization running thousands of daily tests, from targeted regression tests to rare off-nominal scenarios.
• Write and maintain test software, drivers, and interfaces for embedded and Linux-based systems.
• Support test framework architecture designs and improvements.
• Debug complex validation failures spanning simulation, hardware, firmware, and application software
• Collaborate with flight test engineers, systems engineers,  avionics, autonomy and embedded software teams to define system-level validation strategies.
• Improve test reliability, debuggability, and signal-to-noise as systems and test volume scale.

WHAT YOU’LL BRING

• 4+ years of experience in software engineering for complex, hardware-backed, safety-critical systems.
• Extensive experience in Python, specifically using test systems (e.g. pytest)
• Experience testing Rust and/or C embedded systems.
• Extensive experience working with CI/CD.
• Experience developing and executing test plans for complex, safety critical, embedded and cloud software.
• Strong problem-solving and ability to quickly learn a new system for testing purposes

What Else You Need to Know   

The starting cash range for this role is $150,000 - 180,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

CHAOS Industries is redefining modern defense with omniscient systems purpose-built for today’s realities. Designed and built by top U.S. military veterans and Silicon Valley innovators, CHAOS Industries’ products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. In a world where technological threats move at unprecedented speed, CHAOS Industries delivers advanced sensing and detection solutions that give the ultimate advantage: time.   

CHAOS Industries was founded in 2022 and has raised $1B in total funding from leading investors including 8VC, Accel, and NEA. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, Seattle, and London. For more information, please visit www.chaosinc.com. 

The Role

We're looking for a software engineer to build the backend systems that power our sensor infrastructure — the services that ingest, process, and serve data from radar, RF, and other sensing systems at scale. You'll design and operate cloud-native systems on Azure, working alongside systems, hardware, and software engineers in a small team with high autonomy.

This is an early-stage role with outsized impact. You'll define architecture decisions, ship production code, and see your work protecting people's lives.

What You'll Do
- Design and build scalable backend services in Python that process and serve sensor data on Azure
- Architect cloud infrastructure for high-throughput, low-latency data pipelines
- Build and maintain CI/CD pipelines, testing infrastructure, and release processes
- Work directly with hardware and systems engineering teams to integrate software with physical sensor systems
- Define software architecture decisions as a foundational member of the team
- Mentor engineers as the team grows
- Travel periodically to other offices (LA, DC) and customer sites

Requirements
- 3+ years of professional software development experience
- Strong proficiency in Python
- Experience designing and operating scalable backend systems in cloud environments (Azure strongly preferred)
- Track record of building and supporting production systems — you've been on-call, debugged outages, and shipped under pressure
- Proficiency with modern engineering practices: git, unit testing, CI/CD, code review
- Must be a U.S. Person (U.S. citizen or permanent resident) — required for access to controlled technology
- Ability to obtain and maintain a U.S. security clearance

Strongly Preferred
- Experience at a top-tier technology company building systems at scale
- Background building data-intensive pipelines, streaming architectures, or real-time systems
- Experience with infrastructure-as-code, containerization (Docker/Kubernetes), and cloud-native architecture on Azure
- Interest in defense, aerospace, or national security technology

Nice to Have
- Active Secret or Top Secret clearance
- TypeScript/React frontend experience
- 2D/3D data visualization (mapping, geospatial, point clouds)
- Software Defined Radio or RF/IQ data processing experience
- Sensor development background (radars, EO/IR, EW, sensor fusion)
- Additional languages: Rust, Node.js, Java, Bash
- COTS hardware integration experience

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 200 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations.

#LI-onsite

More broadly, Discord is about empowering people to find belonging in all kinds of communities, and those people trust us to keep their communications safe. Our Platform Security Engineering team protects the systems we use to create Discord, making the “secure way” the “easy way.”

We’re looking for a Staff Engineer to advance this mission through security expertise, software development, and operational excellence. In this technical leadership role, you’ll articulate and pursue the most leveraged opportunities to reduce security risk across Engineering, designing and building lovable “paved paths” for managing identities and access, shipping code, configuring cloud infrastructure, and operating services.

If you’re a security engineer who’s deeply curious, eager to own technically and socially complex projects, and excited to improve security and privacy at Discord, read on!

What you'll do

• Shape company-wide security strategy and lead software engineering projects on a highly-autonomous and horizontally-integrated team with a lot of leverage. This is a code-forward role!
• Develop and apply best-in-class secure baselines for cloud infrastructure.
• Secure first- and third-party software supply chains, from the dev environment through CI/CD and into production.
• Build and own identity and access management (IAM) systems that are user-friendly and promote least privilege.
• Manage infrastructure vulnerabilities while supporting rapid growth for Engineering.
• Consult on risk assessments, architectural designs, threat models, code reviews, and more—pragmatically balancing security with other business considerations.

Example projects

• Support IAM with scalable platform solutions (check out https://discord.com/blog/access-a-new-portal-for-managing-internal-authorization).
• Build tooling to prevent and address vulnerabilities across our infrastructure.
• Integrate service-to-service authentication and authorization into Discord’s internal developer platform.

What we look for

• 5+ years of experience building and operating production systems or infrastructure
• 5+ years of experience writing software in a general-purpose programming language (we mainly use Python and Rust)
• 4+ years of experience securing systems with millions of users
• Experience mentoring junior ICs and leading technical projects involving multiple engineers and spanning multiple quarters
• Experience designing and building software for customers (internal or external) beyond your immediate team
• Experience securing cloud environments (e.g. GCP, Cloudflare, AWS)
• Experience defining and orchestrating containers (e.g. via Kubernetes, Docker, Distroless, OCI)
• Familiarity with build and CI/CD technologies (e.g. Terraform, Bazel, Buildkite)
• Understanding of modern authentication and authorization concepts (e.g. RBAC, OAuth, Zero Trust network architectures, mTLS)

Bonus points if you have…

• Developed and debugged distributed systems atop GCP and Cloudflare
• Led complex migrations or risk management programs across an engineering organization
• A system to discover industry tools that can multiply your team’s impact
• Experience securing multi-cloud environments
• Built or operated a service mesh (e.g. Envoy, Istio)
• Managed and secured VMs or bare-metal hosts (e.g. Linux, Salt)

The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

As an Engineer on the Safety Experience team, you’ll help make Discord’s platform safer for hundreds of millions of users. You’ll contribute to designing, building, and maintaining product features and systems that prevent harmful activities while ensuring regulatory compliance. Keeping users safe is essential for Discord’s growth, making your team’s work critical. This role reports to the Engineering Manager of Safety Experience.

What You'll Be Doing

• Contribute to the development of highly visible, user-facing products that protect Discord’s users.
• Design, build, and deploy production APIs, backend services, and data pipelines to launch safety features at scale.
• Collaborate cross-functionally with Product, Design, Policy, Data Science, ML, Legal, and T&S Operations to create solutions that are both impactful and lovable.
• Support rapid responses to the ever-evolving abuse and compliance landscape.

What you should have

• 2+ years of experience writing Python and utilizing back-end API frameworks (Flask, Django).
• 2+ years of experience developing front-end interfaces with JavaScript (React, TypeScript) for both web and mobile platforms.
• Familiarity with databases such as Cassandra, Postgres, and ScyllaDB.
• Ability to contribute to end-to-end delivery of projects: working through ambiguity, participating in rollouts, and communicating with stakeholders.
• Ability to troubleshoot, debug, and test complex systems in a live, production environment.
• Strong communication and collaboration skills, with the ability to work well with cross-functional partners, designers, and other engineers.
• Experience using metrics and dashboards to make data-driven decisions.

Bonus Points

• Interest in the Safety or Anti-Abuse domain.
• Experience analyzing and visualizing data using Datadog or Mode.
• Familiarity with real-time streaming systems like Kafka or Pub-Sub.
• Ability to contribute to offline analytics jobs and processes.
• Experience building and operating mobile-client features on iOS and Android.
• Exposure to lower-level languages such as Go, Rust, and Elixir.
• A strong moral compass that drives you to protect users and do the right thing.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available. For this role, there is no formal requirement to work from the office. The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

The Database Infrastructure team develops and operates all of Discord’s databases and data services. Those systems store the data of Discord's 200M+ monthly active users—including trillions of messages! We work across multiple areas: databases, disk storage and Rust-based data access services. We're a small team whose work has a huge impact on our company's success and ability to grow!

Some blog posts from the team:

• How Discord Indexes Trillions of Messages
• How Discord Stores Trillions of Messages
• How Discord Supercharges Network Disks for Extreme Low-Latency

You will:

• Build and operate large-scale, reliable and performant data systems with ScyllaDB, PostgreSQL, ElasticSearch, Linux and Rust.
• Collaborate with product and infrastructure teams to develop storage primitives enabling all of Discord.
• Exercise "First Principles Thinking" to always deliver what matters most to our users.
• Work with a talented team of engineers who have built one of the largest communication platforms in the world.

You have:

• 2-4 years of experience with building backend infrastructure
• Ability to troubleshoot, debug, and test complex systems in a live, production environment
• Strong operating systems, distributed systems, and concurrency control fundamentals
• Proficiency with at least one statically-typed programming language: e.g. Rust, Go, Java, C, C++
• Comfortable working in fast paced environments

Bonus Points:

• Experience with highly-available and distributed databases: e.g. ScyllaDB, Cassandra, Vitess, Postgres w/HA, etc.
• Experience with Rust
• Knowledge of DevOps tools like Salt, Terraform or Kubernetes

More things that might interest you:

• We’ve tackled a lot of fascinating technical challenges over the years, and blogged about it regularly:
  • How Discord Stores Trillions of Messages
  • 25% or 6 to 4: The 11/6/23 Authentication Outage
  • How Discord Supercharges Network Disks for Extreme Low Latency
  • Why Discord is switching from Go to Rust
  • How Discord Indexes Billions of Messages
  • How Discord Stores Billions of Messages
  • How Discord Indexes Trillions of Messages
• One of our team members even wrote a book on ScyllaDB
• We present at conferences:
  • How Discord Indexes Trillions of Messages by Vicki Niu
  • How Discord Performs Database Upgrades at Scale by Ethan Donowitz

The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

We're looking for a Privacy Engineer to join us in protecting the data of Discord's users and enabling great experiences through responsible data use. We build systems to meet the privacy expectations of our users and enable other teams at Discord to do the same. If you are an engineer with a passion for privacy, a deep sense of curiosity, and an endless desire to improve Discord for our users, read on!

What you will do:

• Ensure user privacy is upheld across all aspects of Discord, from data collection and processing through to deletion.
• Develop technical tools and solutions that advance privacy at Discord, like enhancing privacy review processes through code and dataflow analysis and enforcing data minimization.
• Partner with cross-functional teams, including Engineering, Product, Data, and Legal, to conduct risk assessments, code and design reviews, and ensure compliance with Discord’s Privacy Principles and regulatory requirements.
• Analyze privacy incidents for root causes and work with security and platform teams to ensure we are monitoring for new privacy risks.

What you have:

• A passion for user privacy and data protection.
• 1+ years experience protecting user data and user privacy through tools or processes, such as code review, data mapping, and static analysis. You are familiar with privacy enhancing technologies.
• You have a working knowledge of privacy by design and industry applications of consent, data deletion, and retention.
• You can ship code in at least one general programming language (such as Python, JavaScript, Go, or Rust)

Bonus Points:

• You are familiar with privacy threat models like LINNDUN
• You have experience applying statistical privacy techniques like k-anonymization
• You are familiar with using modern AI tooling to gain leverage in your work
• Experience developing, operating, and debugging distributed systems.
• Experience with modern cloud and data platform infrastructure
• Experience integrating internal systems with privacy and risk management platforms

The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

As a Senior Engineer on the Safety Experience team, you'll lead the charge in making Discord's platform safer for hundreds of millions of users. You'll design, build, and maintain product features and systems that prevent harmful activities while ensuring regulatory compliance. Keeping users safe is essential for Discord's growth, making your team's work critical. This role reports to the Engineering Manager of Safety Experience.

What you'll be doing:

• Lead development of highly‑visible, user‑facing products that protect Discord's users.
• Design, build, and deploy robust production APIs, backend services, and data pipelines to launch safety features at scale.
• Collaborate cross‑functionally with Product, Design, Policy, Data Science, ML, Legal, and T&S Operations to create solutions that are both impactful and lovable.
• Iterate on in-house tooling to supercharge our T&S workflows.
• Respond rapidly to the ever‑evolving abuse and compliance landscape.

What you should have:

• 5+ years experience writing Python and utilizing back-end API frameworks (Flask, Django).
• 5+ years experience developing front-end interfaces with JavaScript (React, TypeScript) for both web and mobile platforms.
• Familiarity with databases such as Cassandra, Postgres, and ScyllaDB.
• Demonstrated success leading end‑to‑end delivery of complex projects: breaking down ambiguity, coordinating rollouts, and aligning stakeholders.
• Demonstrated ability to troubleshoot, debug, and test complex systems in a live, production environment.
• Exceptional communication and collaboration skills, with the ability to work well with cross-functional partners, designers, and other engineers.
• Experience using metrics and dashboards to make data-driven decisions and develop insightful reports.
• Experience utilizing AI tools like Claude Code and Cursor to supercharge dev workflows

Bonus Points

• Experience in the Safety or Anti‑Abuse domain.
• Experience analyzing and visualizing data using Datadog or Mode.
• Familiarity with real‑time streaming systems like Kafka or Pub-Sub.
• Ability to contribute to offline analytics jobs and processes.
• Experience building and operating mobile‑client features on iOS and Android.
• Exposure to lower‑level languages such as Go, Rust, and Elixir.
• A strong moral compass that drives you to protect users and do the right thing.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Discord is looking for a Senior Software Engineer to build high-performance, cross-platform client software that powers experiences for 200+ million users worldwide. You'll work on core libraries that run across Windows, Mac, Linux, Android, and iOS—writing native code using platform-specific APIs to provide optimal experiences wherever people use Discord.

As a Senior Software Engineer on our A/V Client team, you'll tackle challenging performance problems, design systems that scale across diverse hardware configurations, and build the foundation that enables real-time experiences for millions of concurrent users.

What you'll be doing:

• Build core libraries that power Discord's client experiences across desktop, browser, and mobile platforms (Rust, C++, and Typescript)
• Optimize performance end-to-end across all supported platforms
• Design and run experiments with proper success criteria and statistical rigor to validate improvements
• Debug complex issues across diverse hardware and platform configurations
• Collaborate with cross-functional teams to ship features that delight millions of users

What you should have:

• 4+ years building large-scale, cross-platform software (Windows, macOS, Android, iOS, or game console development)
• Strong Rust or C++ skills with deep understanding of memory management, multi-threading, and low-level optimization
• Experience building performance-critical applications where milliseconds matter

Bonus points:

• Experience designing experiments that prove (not just suggest) improvements
• Experience with real-time media applications (audio/video, game streaming, etc.)
• Hands-on experience with WebRTC, SDP, SRTP, or DTLS protocols
• Familiarity with audio/video codecs (Opus, H.264, AV1, etc.) and their corresponding quality measurements (POLQA, PSNR, VMAF, etc.)
• Proficiency with CPU, GPU, and memory profiling—you can identify bottlenecks, optimize critical paths, and manage resource constraints effectively
• You have built or contributed to open source projects

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). For this role, the hiring manager would like folks to be in the office 1 day a week. Relocation assistance may be available. 

The US base salary range for this full-time position is $196,000 to $245,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Discord's Infrastructure organization is the backbone of everything our users experience. From the real-time delivery of 40M+ events per second to storing trillions of messages, our systems power the connections between 200M+ active users. As a Principal Engineer in this organization, you'll operate across our infrastructure teams to shape our technical vision and keep Discord running reliably at massive scale.

This is a role for someone who thrives at the intersection of deep technical expertise and organizational leadership. You'll contribute to the long-term infrastructure roadmap, tackle our most complex and ambiguous technical challenges, and ensure Discord's systems remain reliable, efficient, and ready for the next 200M users.

You will:

• Lead Discord's most critical infrastructure initiatives.
• Define and drive the technical vision and multi-year roadmap for Infrastructure, aligning teams around shared architectural principles.
• Partner with leadership across the company to ensure infrastructure capabilities enable product innovation.
• Design systems that balance reliability, cost-efficiency, and scalability.
• Mentor and grow senior engineers across multiple teams, raising the technical bar organization-wide.
• Represent Discord's engineering culture externally through blog posts, conference talks, and open source contributions.

You have:

• 10+ years of experience building and operating large-scale distributed systems.
• Experience architecting complex infrastructure serving hundreds of millions of users with strict uptime requirements.
• Deep expertise in backend systems, databases, and the operational realities of running systems at scale.
• Ability to navigate significant ambiguity and make sound technical decisions that hold up over time.
• Experience influencing technical direction across many teams without direct authority.
• Strong communication skills and you can articulate complex technical concepts to any audience and build alignment around your vision.
• A passion for mentorship and raising the capabilities of engineers around you.

Bonus points:

• Experience with Rust, Elixir, or Python in production systems.
• Expertise with distributed databases like ScyllaDB, Cassandra, or similar.
• Expertise building large scale chat products.
• History of open source contributions.

Things that might interest you:

• Our languages: Rust, Elixir, and Python.
• Our databases: ScyllaDB, Postgres and Elasticsearch.
• Our systems are deployed in Google Cloud.
• Our infrastructure teams shared many blog posts over the years. Some highlights:
• How Discord Stores Trillions of Messages
• Maxjourney: Pushing Discord’s Limits with a Million+ Online Users in a Single Server
• Modern Image Formats at Discord: Supporting WebP and AVIF
• How Discord Supercharges Network Disks for Extreme Low Latency
• Using Rust to Scale Elixir for 11 Million Concurrent Users
• Why Discord is switching from Go to Rust
• One of our engineers literally wrote the book on ScyllaDB.
• We open sourced some of our work, like our media processing library lilliput, or various Elixir utilities like manifold, sorted_set_nif and more.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). For this role, the hiring manager would like folks to be in the office 1 day a week. Relocation assistance may be available.

The US base salary range for this full-time position is $400,000 to $500,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

What You'll Be Doing

• Lead a team of security engineers who will build and implement application security tools and services, perform secure design reviews and threat modeling, and provide guidance on secure development at Discord.
• Secure our code and development process from IDE to production.
• Scale detection and remediation of security vulnerabilities..
• Work with other Discord teams to limit security exposure to our users, while also shaking out security bugs before they enter production.
• Partner with Discord's product engineering and product management teams to champion new security features for our users.

What you should have

• You have 3+ years of experience as an Engineering Manager and have managed a team of 3+ Security Engineers.
• You have experience programming in at least one general purpose programming language (e.g. Python, Rust, Go).
• You have development-with-AI experience and a good grasp of AI Security practices.
• You have experience leading multiple security projects with a cross-functional group.
• You have experience with tools used to automate vulnerability discovery and remediation.
• You have experience operating in cloud-based environments (we use Google Cloud, but experience with other platforms is ok too).
• You are comfortable writing the roadmap - not just following one.
• You are an expert at reasoning about the security of complex systems, even if they contain components you aren't familiar with.
• Experienced with Threat Modeling and analyzing complex designs.

Bonus Points

• Working knowledge of modern and frequently used cryptographic primitives.
• You have experience with container orchestration technologies (e.g. Kubernetes).
• Experience with Linux system administration.
• You have experience leading multiple security projects with a cross-functional group.
• Familiar with common application vulnerabilities on the platforms Discord ships on (that's all of them).

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Our Web Platform team is responsible for building and maintaining the critical systems that power Discord's frontend development across web, desktop, and mobile platforms. These systems support hundreds of engineers daily, process thousands of builds and deployments, and enable rapid feature delivery through robust tooling infrastructure. Through developing and operating foundational JavaScript build systems - including linters, bundlers, package managers, and CI/CD automation - our work allows internal developers to ship features quickly and safely while ensuring optimal performance, correctness, and developer ergonomics. This team also owns the localization and translation systems that power the strings and copy found across all of our apps and platforms.

As a Senior Software Engineer on this team, you will continuously improve our build tooling, developer workflows, and infrastructure - affecting the productivity of every frontend engineer at Discord and ultimately every user interaction on the platform!

What You'll Be Doing:

• Building and maintaining the tools, pipelines, and processes that keep frontend development at Discord fast, safe, and reliable.
• Becoming an expert in JavaScript tooling and serving as a resource to help teams solve any and all problems they encounter during development.
• Refactoring and upgrading the codebase to pay down tech debt, keep up with the state of the art in web development, and drive progress toward better maintainability.
• Writing new and unique tools based on the specific needs of Discord’s frontend projects to make everything Just Work.
• Digging deep into bundlers, linters, formatters, editor plugins, and more to optimize their performance, adopt and test new features early on, and continuously improve the experience for the developers using them.

What you have:

• 3+ years of working with JavaScript tools and the Node.js ecosystem.
• Familiarity with and a desire to work across multiple programming languages (generally including JavaScript/TypeScript, Python, Rust, Kotlin, Go, and Swift).
• Experience developing and maintaining CLI tools and packages in JavaScript.
• A strong sense for writing maintainable code and deliberately documenting for the future.
• Understanding of all of the tools involved in frontend development and how they work together.

Bonus Points:

• Familiarity and experience with localization in frontend applications.
• Familiarity with React Native, related tools (Metro, Hermes), and bridging between JavaScript and native code.
• Experience with directly maintaining or writing plugins for tools like bundlers, linters, or formatters in any language.
• Experience with CI/CD orchestration, Cloudflare workers, cloud storage providers, and other application deployment processes.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Discord is on a mission to create space for everyone to find belonging. Trusted by millions of people to keep their communications private and out of the hands of evildoers, Security and Privacy are necessary to Discord's success.

We're looking for a Senior Privacy Engineer to join us in protecting Discord's users. If you are an engineer with a passion for privacy, a deep sense of curiosity, and an endless desire to improve Discord for our users, read on!

What You'll Be Doing:

• Build and operate the systems that enable data rights for our users across the data lifecycle, including collection, access, and deletion.
• Own end to end software development of new tools and scalable solutions to optimize the work of the Discord Privacy Program and enable teams to use user data effectively and responsibly in a complex cloud environment.
• Partner with cross-functional teams, including Engineering, Product, Data, and Legal to conduct risk assessments, code reviews, and ensure compliance with Discord’s Privacy Principles and regulatory requirements.
• Advocate for privacy-preserving solutions, act as a privacy subject matter expert across teams, and identify new opportunities to promote our privacy posture.
• Lead Privacy incident response efforts, including mitigating situations that may pose a risk to our Privacy Principles and providing assistance in incident response efforts outside of the privacy domain.

What you should have:

• A passion for user privacy and data protection.
• 3+ years of work experience in Privacy or Security engineering or building production systems that meet legal requirements.
• 3+ years of experience in at least one general purpose programming language (e.g. Python, Rust, Typescript).
• 3+ years of experience working in cloud-based environments (we use Google Cloud).
• Experience with concepts and practices such as threat modeling, data lifecycle management, and data classification
• Familiarity with privacy concerns that apply in an industry setting, including consent, deletion, and retention, and a basic understanding of regulations such as GDPR or CCPA.
• Experience with conducting reviews of system architecture and product feature specs and driving mitigations of data protection risk, deviations from privacy policies, and privacy dark patterns

Bonus Points: 

• Experience developing, operating, and debugging distributed systems.
• Experience with modern data platform infrastructure
• Experience integrating internal systems with privacy and risk management platforms

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

We are seeking an accomplished and experienced Senior Software Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining our data infrastructure and services. You will collaborate with cross-functional teams, including data engineers, data scientists, software engineers, and product managers, to deliver modern and bleeding-edge solutions that drive business insights and innovation. This role reports to our Director of Engineering, Data Platform.

To learn more about Discord’s Data Platform, read our engineering blog — including how we built our modern data stack leveraging open-source tools!

This position is based in our San Francisco office.

What You'll Be Doing

• Define and execute the technical vision for Discord's data platform, enabling scalable, reliable, and performant data systems.
• Design, implement, and optimize data infrastructure to process and analyze petabytes of data across millions of users.
• Develop innovative data architectures to support analytics, machine learning, and operational insights.
• Build monitoring, logging, and alerting systems to ensure the health and performance of data services.
• Partner with data scientists, data engineers, product managers, and leadership to align technical solutions with business goals.
• Promote and drive best practices in data governance, security, and compliance across the organization.
• Provide technical leadership, mentor junior engineers, and foster a culture of excellence and continuous improvement.
• Stay up-to-date with industry trends and emerging technologies in data platform.

What You Should Have

• 5+ years of experience in software engineering with a focus on large-scale distributed systems or data infrastructure.
• Expertise in building and maintaining scalable data platforms, including data ingestion pipelines, stream processing, and batch processing systems.
• Proficiency in programming languages such as Python, Java, Rust, or similar.
• Proficiency with open source data projects and experience working with open source communities.
• Hands-on experience with modern data technologies such as Kafka, Spark, Flink, Airflow/Dagster, or similar.
• Deep understanding of database systems (e.g., SQL, NoSQL, columnar storage) and data modeling principles.
• Strong knowledge of cloud infrastructure (AWS, GCP, or Azure), containerization tools (Docker, Kubernetes), and microservices architecture.
• Excellent communication skills with a demonstrated ability to collaborate and influence across teams and levels.
• Proven ability to thrive in a fast-paced environment.

Bonus Points

• A strong passion for Discord and gaming.
• Open source contributions to data-related projects.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $245,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Our Platform Infrastructure teams are responsible for building and maintaining the critical systems that power Discord's core services. These systems handle hundreds of thousands of requests per second, process tens of billions of transactions daily, and enable millions of users to connect seamlessly. Through developing and operating foundational platform components, our work allows internal developers to rapidly and safely deliver new features to production while ensuring Discord remains reliable, efficient, and scalable.

As a Senior Software Engineer on these teams, you will continuously improve our codebase, processes, and infrastructure - affecting nearly every interaction users have on Discord!

What You'll Be Doing:

• Ensure the reliable and efficient operation of critical systems that serve millions of users daily.
• Design, develop, and scale distributed systems from the ground up.
• Write code and manage infrastructure to support high-performance services.
• Enable dozens of teams to deploy code to production quickly and safely.
• Use and enhance observability tools to troubleshoot complex issues.
• Instrument services to establish robust data collection and monitoring pipelines.
• Coach and mentor other engineers, enabling their development.
• Become a vital part of a small team of talented engineers passionate about keeping Discord running smoothly.

What you have:

• 5+ years of experience designing and developing backend systems.
• Experience scaling distributed systems.
• Experience operating complex services in a production environment.
• Familiarity with open source software, and the ability to dig into a library's source code to find the answer you're looking for.
• Confidence in making tradeoffs when leading projects to ensure constant progress.

Bonus Points:

• Experience with Python or Rust.
• Experience deploying and managing containerized applications with Kubernetes.
• Experience with Google Pub/Sub or other message queue systems.
• A deep understanding of Python runtime internals or the gevent library.
• Experience utilizing AI tools like Claude Code and Cursor to supercharge dev workflows
• You have built or contributed to open source projects.
• You are a Discord power user and have built bots or apps interacting with our platform.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Every day, hundreds of millions of gamers gather on Discord to hang out, strategize their next raid, celebrate tournament victories, and build communities around the games they love. Behind every voice channel, every streamer Go Live, every Quest completed, there's data, petabytes of it, telling the story of how people connect through gaming.

We're looking for someone who gets excited about building data infrastructure at massive scale and cares deeply about the gaming communities we serve. Someone with passion for building lovable products for Discord users and Discord engineers. We’re building the next generation Data Platform that powers decisions for one of the most vibrant platforms in the world.

If you're the kind of Software Engineer who lights up when talking about distributed systems, cares deeply about user privacy, grounding decisions in data, and wants your work to directly impact millions of gamers worldwide, we want to talk to you.

To learn more about Discord’s Data Platform, read our engineering blog, including how we built our modern data stack leveraging open-source tools!

What You'll Be Doing

• Build and maintain data infrastructure processing petabytes of data across millions of users
• Write clean, well-tested code for data ingestion, transformation, and serving systems
• Own projects end-to-end with guidance from senior engineers. From design through deployment and production support
• Collaborate with data scientists, engineers, and product teams to deliver solutions that power Discord's insights

What You Should Have

• 3+ years of software engineering experience with strong programming skills in Python, Java, Rust, Go, or similar
• Solid CS fundamentals and demonstrated ability to quickly learn new technologies and ramp up on unfamiliar systems
• Proven debugging skills and growth mindset. You seek feedback and continuously improve
• Strong collaboration skills and ability to clearly explain technical concepts to different audiences

Bonus Points

• Passion for Discord and gaming
• Experience with the data ecosystem: pipelines, ETL, modeling, or warehousing (Kafka, Spark, Flink, Airflow, Dagster, SQL, etc.)
• Cloud infrastructure knowledge (AWS, GCP, Azure) or containerization (Docker, Kubernetes)

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

We are looking for an experienced Senior Enterprise Security Engineer reporting to the Engineering Manager of Enterprise Security. In this role, you will implement and maintain Discord’s enterprise environment, with a sharp focus on security and privacy. Are you passionate about balancing strong security with seamless operations? We’d love to meet you. We’re looking for someone who brings strong technical skills and genuinely cares about protecting data and keeping systems secure. If you love solving challenging security problems, get energized by learning new things, and want to help make Discord even better, come join our security team on this journey.

What You'll Be Doing

• Design and implement security measures to protect company data from unauthorized access, disclosure, and misuse.
• Partner closely with the Detection & Response team to maintain full visibility into enterprise access, networks, and devices.
• Deploy and manage security tools across Discord's corporate infrastructure.
• Establish security standards that provide strong protection while enabling smooth workflows.
• Develop and deliver security awareness training for employees.
• Shape and enforce Discord's IT and security policies.
• Build secure, sustainable environments using modern principles like "secure by design" and “zero-trust” network architecture, without relying on traditional VPN setups.
• Foster a security-conscious culture by guiding employees on data protection best practices.
• Partner cross-functionally with IT, Engineering, Workplace, and other teams to achieve security objectives

What you should have

• 3+ years of experience in an Enterprise Security role as a senior individual contributor or lead.
• 3+ years of experience programming in at least one general purpose programming language (e.g., Python, Go, Rust).
• Experience securing, monitoring, and managing Identity and Access Management systems (we use Okta, Kolide, Teleport, and Cloudflare Access).
• Deep understanding of data security in enterprise environments.
• Experience working in “zero-trust” network architecture environments.
• Experience deploying and managing Mobile Device Management, Endpoint Detection and Response, and device trust tooling.
• Knowledge and practical application of IT security best practices.
• A great sense of empathy.

Bonus Points

• Experience working with SIEMs (we use Panther)
• Hands on experience with Google Cloud.
• Hands on experience with Cloudflare.
• Hands-on experience managing a primarily macOS and ChromeOS environment with a smaller Windows footprint. We used Jamf & Intune for our endpoint management and Crowdstrike & Jamf for endpoint detections and response (EDR).

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available. For this role, the Hiring Manager would like folks to be in the office 1-2 days a week. The US base salary range for this full-time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

As a Staff Engineer on the Safety Experience team, you'll be a technical leader who autonomously delivers real business impact on large, ambiguous projects. You'll design and build product features and systems that prevent harmful activities at scale while ensuring regulatory compliance. This role requires both deep technical expertise and the ability to be a force multiplier for your team: driving engineering excellence, making solid technical decisions, and remaining a top code contributor. You'll work cross-functionally to shape the technical direction of safety initiatives that protect hundreds of millions of Discord users. This role reports to the Engineering Manager of Safety Experience.

What You'll Be Doing

• Lead development of high-impact, user-facing safety products that deliver measurable results for Discord's users.
• Own complex, multi-milestone projects end-to-end, identifying optimal solutions, navigating ambiguity and making independent technical decisions.
• Design, build, and deploy robust production APIs, backend services, and data pipelines that enable safety features to scale efficiently.
• Collaborate cross-functionally with Product, Design, Policy, Data Science, ML, Legal, and Trust & Safety Operations to create solutions that are both impactful and lovable.
• Drive engineering excellence by mentoring others and guiding the team through architectural challenges to ensure long-term scalability.
• Respond rapidly to the ever-evolving abuse and compliance landscape with strategic thinking and swift execution.

What you should have

• 8+ years of relevant industry experience, with demonstrated ability to deliver high-quality, high-impact work on complex projects.
• Strong expertise in Python and back-end API frameworks (Flask, Django).
• Strong front-end development skills with JavaScript (React, TypeScript) for web and mobile platforms.
• Significant experience in the Safety or Anti-Abuse domain with deep understanding of trust and safety challenges at scale.
• Proven track record of owning large projects end-to-end with varying degrees of ambiguity, breaking down work into well-prioritized milestones with clear dependencies.
• Demonstrated ability to make independent technical decisions that balance short-term needs with long-term sustainability and scalability.
• Experience driving engineering excellence: setting quality standards, conducting thorough code reviews, and applying an adversarial mindset to identify security, performance, and scaling issues.
• Strong communication skills with ability to provide high-quality technical feedback, drive alignment across stakeholders, and facilitate productive debates that lead to clear decisions.
• Experience using metrics and dashboards (e.g., Datadog, Mode, Faros) to make data-driven decisions and monitor system health.
• Ability to be a force multiplier for your team by mentoring others, establishing best practices, and helping teammates grow their skills.
• Experience utilizing AI tools like Claude Code and Cursor to supercharge dev workflows

Bonus Points

• Familiarity with databases such as Cassandra, Postgres, or ScyllaDB.
• Experience with real-time streaming systems like Kafka or Pub-Sub.
• Track record of building and operating native mobile features on iOS and Android.
• Experience designing and implementing monitoring strategies and on-call/on-point processes for production systems.
• Knowledge of lower-level languages such as Go, Rust, or Elixir.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $248,000 to $310,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

We’re looking for a Staff Software Engineer to join our Safety Processing team. This team plays a crucial role in ensuring trust and safety across Discord, processing signals from user reports and automated systems to identify and remove harmful or illegal content from our platform. You’ll lead backend projects, provide architectural guidance, and help build scalable systems that protect our users. Your work will directly impact the safety of our platform and help make Discord a place where everyone can belong. To learn more about Discord Engineering, take a look at our engineering blog.

What You'll Be Doing:

• Lead, design, and build scalable backend systems for processing safety-related signals, primarily using Python
• Guide and mentor the team through architectural and system design challenges, ensuring long-term scalability as Discord continues to grow
• Collaborate with cross-functional teams to build tools for content moderation and related compliance efforts. This includes in house solutions and vendors
• Implement and enhance ML/AI models and automation to improve efficiency in content moderation and decision-making processes
• Build solutions with an adversarial mindset, anticipating and addressing safety challenges such as malicious behavior and illegal content on the platform
• Drive workstreams and provide leadership to the team, mobilizing others to accomplish projects and deliver impactful outcomes

What We Look For:

• Python Expertise: Extensive experience developing and maintaining backend systems using Python
• Architectural Leadership: Strong system design and architecture skills with the ability to build scalable, reliable systems for content moderation with an emphasis on large scale projects, programs, or initiatives measured in quarters or years
• Leadership in Execution: Ability to define workstreams, lead projects, and guide other engineers through implementation
• Adversarial Mindset: Experience in a domain that required an adversarial mindset such as trust, safety, security, or privacy
• On-Call Experience: Experience being in a 24/7 on-call rotation for production systems

Bonus Points:

• Experience working with ML/AI models in content moderation
• Familiarity with Typescript/Javascript/React and frontend technologies
• Familiarity with Rust
• Previous experience at companies with a strong focus on safety, security, or trust & safety

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $248,000 to $310,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

About the role

Anthropic runs some of the largest Kubernetes clusters in the industry. We have fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that makes those clusters work.

We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure.

We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow.

Key responsibilities

• Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
• Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us
• Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on
• Build and maintain custom controllers, operators, and CRDs
• Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities
• Collaborate with cloud providers on required features and escalations
• Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures

Minimum qualifications

• Significant software engineering experience building and operating production distributed systems
• Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
• Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters
• Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
• A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
• Strong written and verbal communication; comfort building consensus with internal stakeholders

Preferred qualifications

• Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
• Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
• Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
• Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
• Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
• Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
• 8+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects

About the Role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale — from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the developer acceleration tooling that deeply integrates Claude into engineering workflows.

Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams. 

Responsibilities:

• Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans
• Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
• Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume workloads across all engineering teams
• Own and evolve build environments, package management, and dependency systems to enable fast, reproducible builds
• Define and implement language ecosystem standards, tooling, and frameworks that drive developer productivity across research and production workloads

You may be a good fit if you:

• Have deep experience with build systems, CI/CD pipelines, and/or developer tooling in a large monorepo environment
• Have strong proficiency in Python, Rust and/or Go
• Are obsessed with developer productivity and reducing friction in the software development lifecycle
• Have experience with container orchestration and infrastructure at scale
• Have excellent communication skills and enjoy supporting internal partners to improve their development experience
• Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges

Strong candidates may have:

• 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure
• 3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead
• Experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar) and merge queue management at scale
• Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar)
• Experience with Nix/NixOS/Docker and managing large image / package sets at scale
• Experience building CLI tools, developer-facing services, and GitHub API and automation workflows

Deadline to apply: None. Applications will be reviewed on a rolling basis.

What You’ll Do:

The Storage Engine Team at CoreWeave is responsible for the product capabilities and data plane function of CoreWeave’s managed storage products. We build reliable, scalable storage solutions with segment leading performance. Storage engine works with engineering teams across infrastructure, compute, and platform to ensure our storage services meet the needs of the world’s most demanding AI workloads.

About the role:

• Design and Implement distributed storage solutions to support scaling data intensive AI workloads.
• Contribute to the development of exabyte-scale, S3-compatible object storage and integrate dedicated storage clusters into diverse customer environments.
• Work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency.
• Lead efforts to improve the reliability, durability, security, and observability of our storage stack.
• Collaborate with operations teams to monitor, troubleshoot, and improve storage systems in production environments.
• Set the bar for developing metrics and dashboards to provide visibility into storage performance and health.
• Analyze telemetry and system data to drive improvements in throughput, latency, and resilience.
• Work cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.
• Share your knowledge and mentor other engineers on best practices in building distributed, high-performance systems.

Who You Are: (This section has to be the technical and measurable requirement of the role, soft skills cannot be measured) 

• Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or a related field.
• 8–10+ years of experience working in storage systems engineering or infrastructure.
• Strong hands-on experience with object storage or distributed filesystems in production environments.
• Experience with one or more storage protocols (e.g. S3, NFS) and file systems such as Ceph, DAOS, or similar.
• Proficiency in a systems programming language such as Go, C, or Rust.
• Proficiency leveraging AI tools to augment software development.
• Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
• Experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love to grow and push the boundaries of your expertise
• You’re curious about distributed storage and the demands AI/ML workloads
• You’re an expert in data persistence on physical media, high performance data transfer using RDMA, or resilient distributed systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do:

The Storage Engine Team at CoreWeave is responsible for the product capabilities and data plane function of CoreWeave’s managed storage products. We build reliable, scalable storage solutions with segment leading performance. Storage engine works with engineering teams across infrastructure, compute, and platform to ensure our storage services meet the needs of the world’s most demanding AI workloads.

About the role:

• Design and Implement distributed storage solutions to support scaling data intensive AI workloads.
• Contribute to the development of exabyte-scale, S3-compatible object storage and integrate dedicated storage clusters into diverse customer environments.
• Work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency.
• Lead efforts to improve the reliability, durability, security, and observability of our storage stack.
• Collaborate with operations teams to monitor, troubleshoot, and improve storage systems in production environments.
• Set the bar for developing metrics and dashboards to provide visibility into storage performance and health.
• Analyze telemetry and system data to drive improvements in throughput, latency, and resilience.
• Work cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.
• Share your knowledge and mentor other engineers on best practices in building distributed, high-performance systems.

Who You Are: 

• Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or a related field.
• 8–10+ years of experience working in storage systems engineering or infrastructure.
• Strong hands-on experience with object storage or distributed filesystems in production environments.
• Experience with one or more storage protocols (e.g. S3, NFS) and file systems such as Ceph, DAOS, or similar.
• Proficiency in a systems programming language such as Go, C, or Rust.
• Proficiency leveraging AI tools to augment software development.
• Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
• Experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love to grow and push the boundaries of your expertise
• You’re curious about distributed storage and the demands AI/ML workloads
• You’re an expert in data persistence on physical media, high performance data transfer using RDMA, or resilient distributed systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $143,000 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do:

The Runtime & GPU Systems team builds and operates secure, high-performance environments for multi-tenant Kubernetes platforms at scale. Our team sits at the intersection of container runtimes, lightweight virtualization, GPU infrastructure, and Linux systems engineering. We partner closely with security, platform, and GPU infrastructure teams to deliver robust, isolated, and efficient execution environments for AI-driven workloads.

About the role:

As a GPU & Runtime Systems Engineer, you will design, build, and evolve secure sandboxed runtime environments for Kubernetes workloads, focusing on runtime isolation, performance, and security. You will integrate container runtimes, lightweight VMs, and virtualization technologies to support GPU-accelerated workloads in multi-tenant environments. Day-to-day, you’ll develop GPU-aware sandboxing and scheduling strategies, optimize containerization and I/O performance for latency-sensitive workloads, and influence architectural decisions across Linux internals, container runtimes, virtualization layers, and GPU drivers.

Some of what you’ll work on:

• Design and implement secure execution environments for containerized and virtualized workloads.
• Build GPU-aware scheduling, isolation, and resource management strategies for multi-tenant workloads.
• Optimize container, VM, and I/O performance across GPU-accelerated workloads.
• Conduct profiling, benchmarking, and performance tuning for runtime, virtualization, and GPU stacks.
• Contribute to architectural decisions across Linux internals, container runtimes, virtualization layers, and GPU drivers.
• Collaborate with security, platform, and infrastructure teams to define and implement runtime isolation and performance standards.

Who You Are:

• 3+ years of experience in systems, platform, infrastructure, or production engineering at scale.
• Strong hands-on experience with Kubernetes, container orchestration, and cloud-native architectures, including controllers, operators, or scheduling extensions.
• Experience designing, implementing, or operating secure execution environments (container runtimes, sandboxed workloads, or virtualized systems).
• Practical experience with lightweight virtualization and sandboxing technologies (e.g., Kata Containers, gVisor, KubeVirt, QEMU).
• Experience supporting GPU-accelerated workloads in multi-tenant environments, including GPU scheduling, isolation, device passthrough, mediated devices, or virtualization.
• Proficient in systems-oriented programming (Go, C/C++, Rust, Bash) with strong Linux internals knowledge.
• Skilled at diagnosing and resolving complex performance, reliability, or isolation issues across containers, VMs, and infrastructure.
• Experienced in profiling, benchmarking, and tuning performance across runtime, virtualization, and GPU stacks.

Preferred:

• Experience building systems for safely executing untrusted or sensitive workloads in shared environments.
• Familiarity with GPU drivers and low-level virtualization or I/O optimization techniques.
• Experience defining threat models and implementing runtime security policies in multi-tenant systems.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love building high-performance systems that operate reliably under extreme scale and demand.
• You’re curious about the intersection of security, virtualization, Kubernetes, and GPU infrastructure.
• You’re an expert in reasoning about trade-offs between isolation, performance, and operability.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $139,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do:

We’re looking for a Staff Storage Engineer to play a key role in designing, building, and operating the control plane for our high-performance AI storage platform. You’ll help evolve CoreWeave’s storage systems by building reliable, scalable, and high-throughput solutions that power some of the largest and innovative AI workloads in the world. This role involves close collaboration with teams across infrastructure, compute, and platform to ensure our storage services scale automatically and seamlessly while maximizing performance and reliability.

About the role: 

• Design and implement a highly scalable multi-tenant control plane that supports CoreWeave’s growing AI storage and cloud infrastructure needs.
• Contribute to the development of exabyte-scale, S3-compatible object storage, distributed file system and integrate dedicated storage clusters into diverse customer environments.
• Work with technologies such as RDMA, GPU Direct Storage, RoCE, InfiniBand, SPDK, and distributed filesystems to optimize storage performance and efficiency.
• Participate in efforts to improve the reliability, durability, and observability of our storage stack.
• Collaborate with operations teams to monitor, analyze, and optimize storage systems using telemetry, metrics, and dashboards to improve performance, latency, and resilience.
• Work cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.
• Share your knowledge and mentor other engineers on best practices in building distributed, high-performance systems.

Who You Are:  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 10+ years of experience working in storage systems engineering or infrastructure.
• Strong hands-on experience with object storage or distributed filesystems in production environments.
• Experience with one or more storage protocols (e.g. S3, NFS) and file systems such as Ceph, DAOS, or similar.
• Proficiency in a systems programming language such as Go, C++, or Rust.
• Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana).
• Solid understanding of cloud-native infrastructure, Kubernetes, and scalable system architecture.
• Strong debugging and problem-solving skills in distributed, high-performance environments.
• Clear communicator, able to work collaboratively across teams and share technical insights effectively.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

About the role:

We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages. 

You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day.

We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. 

What you'll do: 

Platform Acceleration: We work on maximizing the developer productivity of product engineers at Anthropic. You'll architect and optimize the critical development infrastructure that powers our AI product development, including dev environments, observability, and CI/CD pipelines. You’ll partner closely with product teams to understand their development workflow and eliminate friction points. Your work will have an extraordinary multiplier effect, enhancing productivity across our entire product organization and accelerating our mission.

Service Infra: we build and maintain the core infrastructure that powers Anthropic's engineering organization, from service mesh and observability systems to deployment pipelines and shared libraries. Our work enables product teams to build and operate reliable services at scale, making us a critical force multiplier across the entire company.

Multicloud: We build and maintain the infrastructure that enables Anthropic to operate across multiple cloud providers. We focus on cloud-agnostic tooling, cross-cloud networking, and multi-region deployments.

Auth & Identity: We build and maintain the critical infrastructure that powers identity and authentication across Anthropic's product suite. We work closely with product teams, security, support, and trust & safety as customers. We create scalable solutions for user authentication, authorization, role-based access control, and single sign-on that form the backbone of our company's identity management operations. We maintain a user-centric approach, building reliable systems that our users and company can depend on as we tackle complex challenges at the intersection of security, scalability, and user experience.

Connectivity: Our mission is to make Claude the most connected AI. We own the MCP proxy that routes every tool call and the OAuth and token management that keeps connections authenticated. We're also the core contributors to the MCP spec — now an open standard under the Linux Foundation — and maintain the official Python and TypeScript SDKs. You'll work on problems where reliability and enterprise trust are the bar: token refresh at scale, admin controls that let IT govern what agents can do, proxy infrastructure that stays up when partner servers don't. We ship for claude.ai, Claude Code, Cowork, and the API. Relevant experience includes OAuth, API gateways, multi-tenant platforms, building for enterprise, and MCP.

API Distributability: The Claude API today is a rapidly growing platform serving developers and enterprises at scale—but reaching the next tier of enterprise customers requires transforming how and where we deploy it. The Distributability team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it.

Platform Intelligence: We build the training systems that adapt Claude to specific customer workloads. The core problem is task-specific adaptation: getting the right intelligence, cost, and latency profile for a particular use case, and building toward systems where that adaptation can deepen as the customer's usage grows. We work closely with research on training methods and with agent platform teams on data paths. Relevant experience: ML training infra, production ML pipelines, backend engineering. Finetuning experience is a plus.

You might be a good fit if you:

• Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent 
• distributed systems, cloud-native products, developer tools, or external developer facing products
• Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end 
• Are proficient in Python, Go, Rust, or similar systems languages
• Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking 
• Take full ownership of your work—from design through deployment and operations
• Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings 
• Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to use
• Care about building systems that other engineers love to use

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team.