
Forward Deployed Engineer
Required skills
- Python
- machine learning
- production code
- ML pipelines
- distributed systems
- cloud infrastructure
- containerized workloads
- technical projects
- customers
Nice to have
- AI research
- ICLR 2025
- AI agent
- peer-reviewed literature
- automated researchers
- LLM frontier lab
Role summary
Autoscience Institute is seeking a full-time, onsite Forward Deployed Engineer to integrate their AI research systems into client machine learning environments. This role involves direct customer engagement, deploying AI solutions, and troubleshooting complex ML challenges. The engineer will write production code, work within ML pipelines, debug distributed systems, and collaborate with internal research and engineering teams. Responsibilities include end-to-end deployment ownership, from initial technical discussions to production model improvements. The ideal candidate is a strong, autonomous engineer adept at handling ambiguous problems, with excellent Python skills, experience in ML systems, cloud infrastructure, containerization, and debugging.
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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