Software Engineer, RL Data

Job summary

ABOUT Ant*** Ant***’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Benefits

Qualifications

• We're looking for experienced engineers who own outcomes end-to-end — down to reading transcripts, supporting users, and wrangling vendors.
• Trusted to run key projects: you lead and inspire others, plan workstreams effectively, collaborate with cross-functional stakeholders, and proactively eliminate or escalate blockers.
• Strong software engineering
• Experience with reinforcement learning on LLMs, particularly on the data side: creating evals, environments, rewards, graders, or training data.
• Experience helping organizations use AI more effectively, including integrating with third-party
• for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas!
• However, we aren't able to successfully sponsor visas for every role and every candidate.
• But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
• We encourage you to apply even if you do not believe you meet every single qualification.

Responsibilities

• This is a senior, foundational role on a new team: you'll make architecture decisions the rest of the team builds on, and help shape what we build first.
• Own significant parts of our stack end-to-end, from technical architecture through the unglamorous operational work that makes it succeed.
• Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals, and graders until the output is good.
• Develop and improve QA frameworks to catch reward hacking and ensure environment quality.
• Build interfaces that make collecting human data fast and painless for the people providing it.
• Harden execution environments — sandboxing, snapshotting, tool coverage — so tasks hold up at training scale.
• Embed with the teams and domain experts who use our systems day-to-day, and work with operations, security, and compliance partners to roll our systems out to new users and vendors.
• MINIMUM

Skills

Degrees

Industry

Company size