Posting record
Open 12+ days
- Autoscience's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Autoscience, so its true age is longer.
Last checked Nov 2, 2026.
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Not stated: Pay, real vacancy, AI screening.
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Skills mentioned
About the role
Company Description
At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements
Role Description
We’re looking for a full-time on site role for a Forward Deployed Engineer to bring AutoScience into the most important machine learning environments in the world.
You’ll work directly with customers to understand their ML systems, deploy AutoScience into their infrastructure, and turn ambiguous modeling problems into environments where our automated researchers can run thousands of useful experiments.
This is not a traditional solutions engineering role. You’ll write production code, work inside real ML pipelines, debug distributed systems, reason about machine learning challenges, and collaborate directly with our research and engineering teams to make the core product better.
You’ll own deployments end-to-end from the first technical conversation to the first model improvement shipped into production.
Qualifications
- You’re an unusually strong engineer who likes operating where the problem is poorly specified. You bring strong interpersonal judgment and communication skills, build trust with teammates and stakeholders, and collaborate effectively across different working styles and areas of expertise.
- You get enjoyment from socializing with technical and non-technical customers
- You should be comfortable opening an unfamiliar ML repository, understanding how the system works, getting it running, identifying what matters, and shipping something useful quickly.
You likely have
- Strong software engineering fundamentals and excellent Python skills.
- Experience building, training, evaluating, or deploying machine learning systems.
- Experience working with production cloud infrastructure and containerized workloads.
- Strong debugging skills across software, infrastructure, data, and ML systems.
- Experience owning technically complex projects from an ambiguous starting point through production.
- Good judgment about when to build something robust and when to move quickly.
- The ability to communicate deeply technical ideas with researchers, engineers, and technical leaders.
- An eagerness to spend significant time working directly with customers.
- A high degree of autonomy and comfort working in a fast-moving environment.
Benefits & Perks
- Our comp is competitive against major LLM frontier lab packages
- Unlimited PTO and flexible working arrangements
- Conference attendance and publication support
Our Culture
We're a team of passionate researchers and engineers working to automate scientific discovery. We believe in the power of AI to accelerate scientific discovery and are committed to responsible AI development.
We are an e-verify employer.
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