Tech Lead, AI Safety

Trajectory Labs; Berkeley (CA); Hybrid; USD 250,000 - 400,000; Full time

Benefits offered by this job

Health coverage

401(k)

Food: Catered meals & snacks

Relocation assistance

Job summary

Trajectory Labs is hiring a Tech Lead in Berkeley, CA to build a software factory for safety data used to train and evaluate powerful AI models. You will lead researchers to create training datasets, environments, and evaluations, owning the architecture and final outcomes.

You’ll collaborate with frontier labs, handle tough technical problems, and navigate an early-stage startup with evolving priorities and significant impact potential.

Qualifications

• Impact-driven focus on frontier AI safety.
• Experience using coding agents and LLMs as core tools.
• Ability to turn vague research objectives into concrete plans.

Responsibilities

• Lead a team of researchers and contractors to build training datasets, environments, and evaluations.
• Own methodology, system architecture, production code, quality bar, and final results.
• Shape safety decisions and processes for training data and evaluation pipelines.

Skills

Impact-driven

Agent-native engineering

Autonomy & judgment

Startup mindset

AI safety familiarity

Robust collaboration

Job description

Overview

Trajectory Labs is hiring a Tech Lead to build a software factory that produces safety data to train, evaluate, and improve the world's most powerful AI models. You'll partner with researchers at frontier AI labs to build training datasets, environments, and evaluations that help make their models safer.

We're looking for an experienced engineer who uses coding agents extensively and wants to own difficult technical problems, from the first experiment through to reliable systems that researchers can use.

This is an early-stage startup role, so you should expect and enjoy being in a role where responsibilities can grow and priorities can quickly change.

About us

Safety data needs to keep pace with capabilities. As AI advances, we build evaluations that measure consequential agent failures and produce training data that helps mitigate them.

Although we're only a year old, we've already been featured in Anthropic's Fable 5 & Mythos 5 System Card, led Anthropic's prompt injection evaluation of Auto mode, and been featured in Meta's Muse Spark Safety & Preparedness Report.

Our areas of focus include red teaming, control, anti-distillation, AI safety reasoning, reward-hacking propensity evaluations, and embedded assessments.

A lot of companies say they use AI extensively. We mean it. PR count isn't the goal, but to give a concrete example, last week a single engineer merged 1,000 PRs.

About the role

You'll partner directly with researchers at frontier AI labs to solve crucial safety and alignment problems. You'll lead a team of researchers and contractors to build training datasets, environments, evaluations, and the tools labs need to use them. You'll own the methodology, system architecture, production code, quality bar, and final results.

Projects span both diagnosing and improving model behavior. You might build an evaluation that measures an important failure mode, or develop an RL environment or training dataset that helps correct it.

You'll work closely with our founders and the teams developing frontier models, with unusual autonomy to make consequential technical and operational decisions. The projects you lead will shape system cards, safety decisions, and how the world's most capable AI systems are trained.

What we're looking for

Essential

• Impact-driven: you want to improve the safety of frontier AI systems.

• Agent-native engineering: you use coding agents and LLMs as core development tools.

• Autonomy and judgment: you can turn a vague research objective into a concrete plan, make good trade-offs, and keep the work moving with minimal direction.

• Early-stage startup drive: you enjoy a fast pace, shifting priorities, limited structure, and taking on whatever is most important to help the company succeed.

Desirable

• Experience working in an AI safety or alignment context

• Experience building evals, red-teaming systems, RL environments, or model-training data

• Experience collaborating with frontier labs or other demanding technical customers

Logistics

Total compensation: Includes base salary, bonus, and the estimated annualized value of equity. Your level depends on the scope, autonomy, and impact we expect you to have:

• L4: $350,000

• L5: $520,000

• L6: $670,000

• L7: $900,000

Base salary: $250,000–$400,000 per year.

Location and workspace: Our team works out of Constellation in Berkeley, CA, and we prefer someone who can work alongside us there. We are open to remote for the right candidate.

Benefits:

• Health coverage: You'll receive a generous monthly pre-tax allowance to choose the medical, dental, and vision coverage that best fits your needs.

• 401(k): We offer a 401(k) retirement plan with a company match.

• Food: Catered lunch and dinner, unlimited snacks and drinks.

• Relocation: A generous moving allowance to relocate to Berkeley.

Visa sponsorship: We sponsor visas, although we cannot successfully sponsor every visa for every role or candidate. If we make you an offer, we will make every reasonable effort to secure the visa you need, with support from an immigration lawyer we retain to guide and coordinate the process.

Reports to: Ben West, CTO.