HUD - Research Engineer (General)

Remote - Singapore, United States - Asia-Pacific *$80k - $230k6mo ago

Remote NA Artificial Intelligence Logistics Research Engineer Python Docker Linux Revenue Growth Data Quality

Requirements

• Proficiency in Python, Docker, and Linux environments • Worked with large-scale datasets • Evidence of rapid learning and adaptability in technical environments (e.g., programming competitions) • Startup experience in early-stage technology companies with ability to work independently in fast-paced environments • Familiarity with current AI tools and LLM capabilities • Strong communication skills for remote collaboration across time zones • Strong candidates may also: • Understand of common failure modes in training data • Have experience building data validation pipelines and/or human-in-the-loop review systems • Be detail-oriented and able to spot subtle inconsistencies or edge cases in data • Be comfortable designing metrics, experiments, and QA processes, not just executing them • We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. • Team & company details • Team Size: ~15 people currently, mostly full-time in-person, but some remote. • Team Size • Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. • Our team: • Company stage: We have 8 figures in funding and high revenue growth. We’re scaling profitably and quickly to meet very strong demand. • Company stage: • Logistics • Logistics • Employment: Full-time. • Employment • Location: On-site in the San Francisco Bay Area. • Location • Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US. • Timeline: Applications are rolling. The process is 2 technical interviews and a 1-week work trial. • Timeline

Responsibilities

• Define and enforce quality standards for training data • Build tooling and workflows to audit supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops • Determine if and how human-in-the-loop review workflows can be used to optimize QA • Partner with data vendors to debug quality issues, provide actionable feedback, and improve their data generation processes • Continuously integrate QA learnings into infrastructure tools and data vendor portal to reduce anomalies, inconsistencies, and edge cases

Benefits

• Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • We will contact you via this email during the application process. • or drag and drop here • Please ensure to provide your LinkedIn profile or Resume, we require at least one of the two. • Or any other examples of technical experience (Codeforces / Leetcode etc.) • Or Arxiv, OpenReview, Hugging Face etc. • Or anything else we'd find interesting. • Or something you did that you were proud of. Be specific. • Enter your current location. This is mainly for coordinating calls/meetings for the application process, and for any future logistics. • Select “Yes” if the position is exclusively on‑site, AND you will need employer sponsorship to obtain or maintain legal authorization to work in that location. • “Yes” • exclusively on‑site, • Select “No” if the role offers a remote option you intend to take, OR you already have, or can independently secure, authorization to work on-site without employer assistance. • remote • without • Your response is gathered solely to understand potential immigration requirements. It will not disqualify you from consideration. If you are selected for the role, we will work with you, consistent with applicable laws and company policies, to pursue any required sponsorship. • Anything else you want us to know, or any questions/feedback.