About the Role

We are hiring a developer productivity engineer to advance how we build software internally: safely, quickly, and with delight. The main focus are AI tools and coding agents. You’ll partner with platform, security, and product engineers to build state-of-the-art tooling for AI-assisted software development, and make our inner loop dramatically faster. 

The scope of this role includes both setting up company-wide platforms and working with developers to accelerate their individual workflows. 

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

• Enable our researchers and engineers to leverage AI to improve coding productivity without compromising code quality
• Standardize AI coding tools, such as Claude Code, Cursor, and Codex. You will help configure, harden, and maintain the best tools, integrating org-wide configurations with individual preferences.
• Build secure, reproducible agent sandboxes for remote dev & CI testing.
• Set up golden-path dev environments and guardrails for secrets/PII.
• Help individual contributors develop their personalized AI-enabled workflow.
• Track tool usage, reliability, and cost.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent industry experience in computer science, engineering, or similar.
• Experience developing productivity tools and best practices for large codebases.
• Ability to communicate clearly and work with researchers to build and manage a variety of internal tools.

Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but at least some:

• Hands-on experience with container platforms (e.g. Docker/Kubernetes), modern CI (GitHub Actions/Buildkite), and package management tools (uv).
• Practical experience with AI coding tools and model APIs (e.g. OSS via vLLM / SGLang / TGI).
• Solid Linux/networking fundamentals; comfort with secrets management and safe egress.
• Proficiency in systems programming languages (e.g. Rust) and scripting languages (e.g. Python).

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About the Role

We’re looking for an engineer to join us and contribute to data infrastructure. You'll join a small, high-impact team responsible for architecting and scaling the core infrastructure behind distributed training pipelines, multimodal data catalogs, and intelligent processing systems that operate over petabytes of data.

Infrastructure is critical to us: it's the bedrock that enables every breakthrough. You'll work directly with researchers to accelerate experiments, develop new datasets, improve infrastructure efficiency, and enable key insights across our data assets.

If you're excited by distributed systems, large-scale data mining, open-source tools like Spark, Kafka, Beam, Ray, and Delta Lake, and enjoy building from the ground up, we'd love to hear from you.

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

• Design, build, and operate scalable, fault-tolerant infrastructure for LLM Research: distributed compute, data orchestration, and storage across modalities.
• Develop high-throughput systems for data ingestion, processing, and transformation — including training data catalogs, deduplication, quality checks, and search.
• Build systems for traceability, reproducibility, and robust quality control at every stage of the data lifecycle.
• Implement and maintain monitoring and alerting to support platform reliability and performance.
• Collaborate with research teams to unlock new features, improve data quality, and accelerate training cycles.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Are fluent in distributed compute frameworks such as Apache Spark or Ray.
• Are deeply familiar with cloud infrastructure, data lake architectures, and batch and streaming pipelines.
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Have hands-on experience with Kafka, dbt, Terraform, and Airflow.
• Have experience building a web crawler.
• Have extensive experience understanding and scaling deduplication, data mining, and search.
• Have strong knowledge of file formats and storage systems (e.g., Parquet, Delta Lake, etc.) and how they impact performance and scalability.
• Are proactive about documentation, testing, and empowering your teammates with good tooling.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About Tinker

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use-cases. We’re hiring to grow the platform alongside the Tinker community.

About the Role

We're looking for a Site Reliability Engineer to drive the reliability of Tinker end-to-end. You'll work alongside the engineers building the platform and research teams to make every layer of the system more robust and resilient. 

What You’ll Do

• Define and own end-to-end reliability, from CI/CD flows to production observability and incident response.
• Develop appropriate Service Level Objectives for distributed training systems, balancing job completion reliability and scheduling latency with development velocity.
• Design and implement monitoring and observability across the full training path.
• Drive incident response for Tinker platform issues, ensuring rapid recovery, thorough incident reviews, and systematic improvements that prevent recurrence.
• Harden multi-tenant isolation and resource scheduling so that LoRA-based workload co-scheduling maximizes utilization without compromising reliability or data separation
• Collaborate with security teams to address production vulnerabilities

Skills and Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent experience in computer science, engineering, or similar.
• Experience in distributed systems, cloud infrastructure, or site reliability engineering.
• Proficiency writing software to solve reliability problems, including building tooling and automation.
• Experience with production incident response, postmortems, and systematic reliability improvement.
• Strong communication skills and track record of coordination across engineering and research teams.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Deep experience operating production cloud services at scale (e.g., public cloud platforms, internal cloud services)
• Background in distributed training frameworks and how infrastructure failures surface in training behavior.
• Track record building checkpoint and recovery systems for long-running distributed jobs.
• Expertise in Kubernetes at scale: deploying, operating, debugging, and tuning clusters handling heterogeneous GPU workloads.

Logistics

• Location: This role is based in San Francisco, California.
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 – $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About Tinker

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use-cases. We’re hiring to grow the platform alongside the Tinker community.

About the Role

We're hiring a Forward Deployed Engineer to be the main point of contact with our customers, which range from individual hackers to major enterprises. You will diagnose their problems and needs and turn those into product improvements, taking ownership of both ends of this process.

What You’ll Do

• Triage and resolve customer issues across the full stack, reading logs, reproducing failures, and tracing job execution.
• Build tools, integrations, and automation that eliminate recurring failure modes and reduce time-to-resolution for users.
• Write and maintain high-quality documentation and cookbook recipes, grounded in real issues and implementations from our users.
• Partner closely with research and infrastructure teams to translate customer pain into prioritized engineering work.
• Inform Tinker's product roadmap based on what you learn from working directly with customers every day.
  
  

Skills and Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent experience in computer science, engineering, or similar.
• Experience fine-tuning large language models with supervised and reinforcement learning methods.
• Experience debugging distributed systems and training infrastructure: reading logs, tracing job failures, diagnosing GPU, networking, or scheduling issues.
• Proficiency in at least one backend language (we use Python and Rust).

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• 5+ years of software engineering experience, including work in customer-facing or deployment roles.
• Building or shipping a product end-to-end — a startup, an open-source project, or an internal tool you owned from idea to users.
• Published technical tutorials, recipes, or documentation that helped others get unstuck.
• Experience at a developer tools, API-first, or ML platform company.
• Familiarity with hyperparameter tuning for LLM training algorithms.
• Contributions to open-source ML or infrastructure projects.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About Tinker

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use-cases. We’re hiring to grow the platform alongside the Tinker community.

About the Role

We're looking for a full stack engineer to build and ship the products and services that Tinker users interact with every day. You'll work across frontend, backend, and infrastructure building the Tinker console, developer tools, and whatever Tinker needs most.

What You’ll Do

• Build and extend Tinker's APIs and backend services in Python and Rust, from job submission and orchestration to billing and usage tracking.
• Ship user-facing product surfaces — console and future tools — with React and TypeScript.
• Improve the developer experience for Tinker users: SDK ergonomics, error messages, API design, onboarding flow.
• Improve system reliability, observability, and security across Tinker's production environment; participate in on-call.
• Build internal tooling that accelerates the Tinker research and infrastructure teams.

Skills and Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python and Rust).
• Some familiarity with React, TypeScript, or mobile platforms.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• 4+ years building backend systems in production.
• Experience designing and maintaining backend APIs at scale, especially for developer-facing platforms.
• Experience building tooling or products for ML training, fine-tuning, or inference workloads.
• Familiarity with distributed training infrastructure, job orchestration, and GPU scheduling.
• Ability to build high-quality, production-level UIs from prototype to polish.
• Experience with developer experience work — SDK design, CLI tooling, API ergonomics, documentation.

Logistics

• Location: This role is based in San Francisco, California or New York, New York. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About Tinker

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use-cases. We’re hiring to grow the platform alongside the Tinker community.

About the Role

We're looking for a software engineer to own the platform systems that enable Tinker — billing and usage metering, permissions and access control, organizations and teams, data exports, audit logging, and the admin surfaces that tie them together. This role partners with everyone from product to legal, as every new feature, pricing change, and enterprise deal flows through your work.

What You’ll Do

• Design the authorization layer across all products: RBAC, API key scoping, organization hierarchies, and permission boundaries.
• Own billing infrastructure end to end, including usage metering and aggregation, plan management, payment processing, invoicing, and revenue recognition support.
• Build and evolve the organizations and teams model: seat management, SSO/SAML, workspace isolation, and invite flows.
• Implement data export and deletion pipelines that meet enterprise compliance and data residency requirements.
• Build audit logging so customers and internal teams have clear visibility into who did what, when.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Experience with at least one of: billing/payments infrastructure, identity and access control (RBAC/ABAC, OAuth, SAML), or multi-tenant platform systems.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• 4+ years building backend systems in production.
• Experience building billing or metering systems at scale (Metronome pipelines, usage-based pricing, invoicing pipelines).
• Familiarity with enterprise-readiness patterns: SSO/SCIM provisioning, audit trails, data residency, custom contracts, role hierarchies.
• Strong opinions on building correct financial systems — idempotency, exactly-once semantics, reconciliation.
• Experience with event-driven architectures or stream processing for usage metering.
• Background in security engineering or a strong security mindset (least-privilege design, secure defaults, threat modeling).
• Prior work at an AI/ML company, developer tools company, or API-first platform.

Logistics

• Location: This role is based in San Francisco, California or New York, New York. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About the Role

We’re looking for a full stack engineer to build and ship products from prototype to scale and to maintain tools that accelerate research and product teams. You’ll work across frontend and backend components, and contribute to reliability, observability, and security in production.

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

• Prototype and build new APIs and product backends in Python and Rust.
• Launch new products and UX with React and TypeScript where needed.
• Improve developer experience for local dev, deployment, testing, and iteration speed.
• Improve system reliability, observability, and security across production environments; participate in on‑call.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Some familiarity with ReactJS, TypeScript or mobile platforms.
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Experience designing and maintaining backend APIs at scale.
• Experience building tooling or products for LLMs or other systems that scale to a large number of users.
• Ability to build high‑quality, production-level UIs from prototype to polish.
• Familiarity with NodeJS, Python, and/or Rust.
• Experience building AI products or other products that scale to a large number of users.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About the Role

We’re looking for a software engineer focused on making our products secure by default while supporting fast and ambitious product iteration. You’ll embed with product and research teams to bake security into design and development and to build tooling and automation that keep systems safe at scale.

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

• Partner with product and research teams to embed security into the development lifecycle: threat modeling, design reviews, and secure defaults for new features.
• Design and implement security controls across our product stack (authentication, authorization, session management, input validation, etc.).
• Build and maintain security tooling and automation for engineers: secure frameworks and templates, CI/CD checks, dependency management, and vulnerability detection.
• Collaborate with researchers to identify and mitigate AI-specific product risks, such as model abuse, prompt injection, data leakage, or misuse of capabilities.
• Improve observability and detection for security-relevant events: access anomalies, abuse patterns, and suspicious behavior in production.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Strong generalist software engineering background and ability to review production code for security risks.
• Hands-on experience securing web apps and APIs especially auth flows, access control, secrets management, input validation, and data protection.
• Familiarity with common vulnerability classes and prevention frameworks; experience hardening prototypes into production.
• Comfort with modern cloud infrastructure and understanding how application concerns intersect with infrastructure.
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Experience securing AI‑powered products or working with ML/LLM APIs and their unique threat models.
• Background in human-computer interaction, especially where security or trust plays a central role in the user experience.
• Strong skills in rapid prototyping and iteration, with a habit of turning ad-hoc fixes into reusable patterns and tools.
• Open‑source security work, bug bounty write‑ups, or published tooling.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About the Role

We’re looking for an engineer to design, build, and operate the GPU supercomputing environment that powers large‑scale training and inference. You will deliver high‑performant, reliable, and cost‑efficient compute so our users and researchers can move fast at scale.

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

• Operate and automate large GPU clusters including provisioning, imaging, and capacity planning.
• Write software that abstracts cluster management and presents a unified interface for training and inference.
• Extend scheduling/orchestration (Kubernetes, Slurm, or similar) for topology‑aware placement, preemption, quotas, and fair‑share multi‑tenancy.
• Monitor and improve operational metrics of speed, reliability, and error recovery.
• Build reliable storage and artifact paths for datasets, checkpoints, and logs with clear retention and lineage.
• Partner with researchers to unblock scale runs and advise on parallelism and performance trade‑offs.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Experience operating large‑scale clusters and container orchestration systems (e.g. Kubernetes or Slurm).
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Strong systems background: Linux, networking, and infrastructure‑as‑code.
• Familiarity with CUDA/NCCL and performance profiling for distributed training/inference.
• Prior work supporting large‑scale model training or inference environments.
• Understanding of deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) and their underlying system architectures.
• Track record of working in fast-paced environments balancing care with urgency.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

About the Role

We’re looking for generalist infrastructure and systems engineers to help build the systems that power our foundation models and the internal teams on research and product development to be able to create the models and ship the products powered by our models.

You'll join a small, high-impact team responsible for architecting and scaling the core infrastructure behind everything we do. You’ll work across the full technical stack, solving complex distributed systems problems and building robust, scalable platforms.

Infrastructure is critical to us: it's the bedrock that enables every breakthrough. You'll work directly with researchers to accelerate experiments, improve infrastructure efficiency, and enable key insights across our models, products, and data assets.

Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.

What You’ll Do

We interview generally, but during project selection we’ll take into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the infrastructure teams where they'll have the greatest impact and growth potential.

Here are example areas you may contribute to depending on your area of expertise and interest:

• Core Infrastructure: We support teams that train, research, and ultimately serve AI models and build the underlying infrastructure for the clusters to reliably and safely train frontier models. Examples might include building systems and running large Kubernetes clusters with GPU workloads, or building infrastructure to support Tinker.
• Data Infrastructure: We build and maintain the data systems for our research and products. You'll design and optimize data pipelines using tools like Spark and other modern data infrastructure technologies.  You’ll build scalable, reliable, data infrastructure while embedding governance best practices.
• Developer Productivity: We care deeply about research and engineering productivity and our ability to continue shipping quickly. We build tooling, systems, frameworks, and systems to make sure everyone gets well configured, optimized developer environments.

Skills and Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
• Proficiency in at least one backend language (we use Python or Rust).
• Experience operating large‑scale clusters and container orchestration systems (e.g. Kubernetes or Slurm).
• Comfort operating across the stack and owning projects end-to-end.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

• Strong debugging across application, OS, and network layers.
• Proficiency in Python or Rust (or similar), containers, and modern CI.
• Experience with Kubernetes, controllers/operators, or performance profiling.
• Familiarity with GPU/ML workflows or large‑scale data/eval pipelines.

Logistics

• Location: This role is based in San Francisco, California. 
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.