A Platform Engineer is responsible for the development of platforms that support the needs and use cases of different engineering teams across the organization. Creates reusable tools and workflows to streamline operational needs and facilitate automation tasks, supporting scalability of DevOps practices.
2+ (Possible extension based on performance & business needs) Story Behind the Need -
Business Group & Key Projects:
Client Super Intelligence Labs - ESI Embodiment Team Join the small team building Conductor, the data and operations platform for our robotics program. Conductor manages high-volume, multimodal robot data from ingestion through quality control, discovery, training, and evaluation. You will own meaningful production systems, work directly with researchers and robotics engineers, and ship quickly with a high degree of autonomy. Key Projects / Day-to-Day Responsibilities Build reliable backend services, APIs, and data pipelines using Python and Go across PostgreSQL and AWS/S3. Design systems for ingesting, indexing, transforming, validating, and serving large robotics datasets. Develop agentic and LLM-powered workflows for data quality, enrichment, automation, and research productivity with evaluations and guardrails. Improve performance, observability, correctness, and operational reliability across the platform.
Work end-to-end:
clarify requirements, make pragmatic design choices, implement, test, deploy, and iterate with users.
Skills/Sourcing:
Full stack development, large scale data processing. Must be good with AI assisted coding. Need to have good engineering taste, exp with distributed systems, backend, large scale workloads, etc. Contributions to open-sourced projects - shows initiative on their part (working on a project they are passionate about) core contributor to well known or widely used software (show github profile link) Competitive internships - working with big tech companies (quant, good engineering culture tech): jane street, hrt, google, stripe, databricks, cloudflare, meta, vercel, openai), companies known for having high engineering standards Prioritize graduating students and candidates within two years of graduation from rigorous CS/engineering programs (for example MIT, Stanford, CMU, Berkeley, UIUC, Waterloo, Georgia Tech, UT Austin, Princeton, Cornell, or comparable programs). School is a sourcing signal, not a gate
Must-Have Skills:
Exceptional Software Engineering Fundamentals:
Data structures, algorithms, systems, databases, and debugging. Backend /
Data Systems Experience:
Proven track record building substantial backend, data-intensive, or distributed systems (via internships, research, open source, or ambitious projects).
Languages & Databases:
Strong programming skills in at least one statically typed language (Go) alongside Python and SQL.
Nice-to-have Skills:
Open Source & Research:
Substantial contributions to respected open-source projects or systems/data research. Exceptional software-engineering fundamentals, including data structures, algorithms, systems, databases, and debugging. Evidence of building a substantial backend, data-intensive, distributed, or developer-infrastructure system through internships, research, open source, or ambitious independent/course projects. AI /
Workflows:
Experience building useful agentic workflows with real evaluations. Strong programming skills and experience with at least one statically typed language; working knowledge of SQL. Ability to write clear, maintainable production code and reason carefully about reliability, performance, and data correctness. High ownership, intellectual curiosity, sound judgment, and comfort moving quickly in an ambiguous environment.
Cloud & Infrastructure:
Hands-on experience with Postgre
SQL, AWS/S3, ML
platforms, or developer tools. Especially strong signals Maintaining or making substantial contributions to a respected open-source project; internships on data, infrastructure, databases, ML platforms, or developer tools; building useful agentic workflows with real evaluations; systems research; or exceptional technical projects with real users or meaningful scale. A BS/MS in computer science or a related field from a program with a strong systems culture is helpful, but demonstrated ability matters more than pedigree. Prior robotics experience is not required.
Years of Experience:
Early Career / New Graduate (0-2 years of experience, more is good too)
Degrees/Certifications Required:
BS/MS in Computer Science or a related field (preferably from top systems programs like MIT, Stanford, CMU, Berkeley, UIUC, Waterloo, Georgia Tech, UT Austin, Princeton, Cornell). Demonstrated ability matters more than pedigree. Are there any types of candidate profiles or skills that may not be the right fit for this team? Possible Disqualifiers Lack of strong software engineering fundamentals or programming ability in statically typed languages/SQL. No evidence of building substantial backend or data-intensive systems projects/internships. Inability to demonstrate at least two concrete proof points (selective internship, open source, research, shipped scale project, or competitive programming/systems coursework
