SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Autoscience Institute creates AI systems that autonomously conduct AI research, recently announcing the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops).
You will serve as a Forward Deployed Engineer, working directly with customers to understand their ML systems, deploy Autoscience into their infrastructure, and transform ambiguous modeling problems into environments where 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 research and engineering teams to improve the core product.
You will own deployments end-to-end, from the first technical conversation through the first model improvement shipped into production. You'll be comfortable opening unfamiliar ML repositories, understanding how systems work, getting them running, identifying what matters, and shipping something useful quickly. You'll spend significant time working directly with both technical and non-technical customers, socializing with them and building trust across different working styles and areas of expertise.
This role requires strong interpersonal judgment and communication skills. You'll need to communicate deeply technical ideas with researchers, engineers, and technical leaders, and operate effectively where problems are poorly specified.
QUALIFICATIONS:
- 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 ambiguous starting point through production
- Good judgment about when to build something robust versus when to move quickly
- Ability to communicate deeply technical ideas with researchers, engineers, and technical leaders
- Eagerness to spend significant time working directly with customers
- High degree of autonomy and comfort working in a fast-moving environment
