The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
About the RoleWe’re looking for a detection and response engineer to build how we find, investigate, and stop threats against our company, platforms, models, and data. You’ll own the pipelines that turn raw telemetry into high-fidelity detections, lead the response when real incidents happen, and run a threat intelligence practice that keeps our defenses focused on the adversaries who actually target frontier AI labs. You’ll partner closely with security, infrastructure, research, and product teams so that detection and response scale with the company instead of slowing it down.
What You’ll DoLead incident response end-to-end: triage, scoping, containment, eradication, recovery, and blameless postmortems that turn lessons into new detections and controls.
Design, build, and operate the security data pipelines and tooling that power detection and response: collecting, normalizing, enriching, and storing telemetry from cloud, Kubernetes, identity, endpoint, SaaS, and application sources.
Author, deploy, and maintain high-fidelity detections across SIEM, endpoint, cloud, and security tooling
Build and run our threat intelligence practice: track actors and campaigns relevant to AI labs such as espionage, model weight theft, supply chain compromise, and credential abuse. Turn that intel into hunts, detections, and hardening recommendations.
Proactively hunt for threats across our environment, and build automation and response tooling: enrichment, playbooks, automated containment that shortens time to detect and respond.
Collaborate with researchers and product teams to detect AI-specific threats in production.Develop and exercise incident response plans, on-call processes, and tabletop exercises with engineering, research, legal, and leadership.
Participate in an on-call pager rotation for security incidents.
Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
Proficiency in Python or Rust for building data pipelines, detections, and internal tools.
A track record responding to real security incidents in production environments, including leading investigations and coordinating across teams under pressure.
Hands-on experience building and operating security data pipelines at scale: log ingestion, parsing and normalization, enrichment, and storage and query in a SIEM or data lake (e.g., Splunk, Elastic, Panther, BigQuery, Snowflake, or ClickHouse).
Experience producing and consuming threat intelligence: tracking adversary TTPs, mapping them to frameworks like MITRE ATT&CK, and translating intel into detections and hunts.
Strong understanding of cloud, AWS, GCP, or Azure, Kubernetes, and identity provider telemetry, and how attackers move through these environments.
Familiarity with host and network forensics, including endpoint telemetry, memory and disk analysis, and network logs.
Comfort operating across the stack and owning projects end-to-end.
Clear communication: incident reports, intel briefs, and postmortems for both technical and non-technical audiences.
Detection and response experience at an AI lab, cloud provider, or other high-threat environment targeted by sophisticated actors.
Experience detecting AI-specific abuse, such as prompt injection, model extraction, or anomalous API usage.
Familiarity with ML infrastructure telemetry: GPU clusters, training jobs, and model artifact storage.
Experience with stream processing (e.g., Kafka, Flink, Vector) and cost-aware log management at high volume.
Malware analysis or reverse engineering experience.
Talks, blogs, open-source detection content, or published threat research.
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 $300,000-$350,000 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.
Skills Required
- Bachelor's degree or equivalent experience in computer science, engineering, or a similar field
- Proficiency in Python or Rust for building data pipelines, detections, and internal tools
- Experience responding to real security incidents in production, including leading investigations and coordinating across teams
- Hands-on experience building and operating security data pipelines at scale, including log ingestion, parsing, normalization, enrichment, storage, and querying in a SIEM or data lake
- Experience producing and consuming threat intelligence, tracking adversary TTPs, mapping them to MITRE ATT&CK, and translating intelligence into detections and hunts
- Strong understanding of AWS, GCP, or Azure, Kubernetes, identity provider telemetry, and attacker movement through these environments
- Familiarity with host and network forensics, including endpoint telemetry, memory and disk analysis, and network logs
- Ability to operate across the technology stack and own projects end-to-end
- Clear communication skills for incident reports, intelligence briefs, and postmortems
- Detection and response experience at an AI lab, cloud provider, or other high-threat environment
- Experience detecting AI-specific abuse, such as prompt injection, model extraction, or anomalous API usage
- Familiarity with ML infrastructure telemetry, including GPU clusters, training jobs, and model artifact storage
- Experience with stream processing technologies such as Kafka, Flink, or Vector and cost-aware high-volume log management
- Malware analysis or reverse engineering experience
- Talks, blogs, open-source detection content, or published threat research
What We Do
Thinking Machines Lab is an artificial intelligence research and product company. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. While AI capabilities have advanced dramatically, key gaps remain. The scientific community's understanding of frontier AI systems lags behind rapidly advancing capabilities. Knowledge of how these systems are trained is concentrated within the top research labs, limiting both the public discourse on AI and people's abilities to use AI effectively. And, despite their potential, these systems remain difficult for people to customize to their specific needs and values. To bridge the gaps, we're building Thinking Machines Lab to make AI systems more widely understood, customizable and generally capable. We are scientists, engineers, and builders who've created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
