← All roles

Research Engineer

Training Superintelligence· R&D / Engineering
Apply on company site
Hybrid (Colombia)Posted 3mo ago

About the role

Remote role in Colombia (Colombia, Huila) focusing on delivering frontier-quality datasets, RL environments, and evaluations to improve state-of-the-art models for AI labs and enterprise clients.

Responsibilities

  • Own data and environment quality from an AI researcher perspective: translate ambiguous research goals into clear data requirements, define what good looks like with rubrics and boundary cases, perform deep audits of produced data, and drive iterative improvements using evidence.
  • Design and build datasets and RL environments for your capability area(s): contribute to or lead the design of task suites, ground-truth signals, and environment interfaces; focus areas include Coding/SWE agents, RL environments and verifier-based training, Multimodality, STEM, and Modern embodied AI / VLM-driven agents.
  • Build robust validation, denoising, and synthetic data systems: automated validation and filtering, deduplication, leakage checks, consistency checks, and diversity controls; develop synthetic data generation and augmentation pipelines; create documentation and data cards.
  • Use evaluations and training runs to prove impact: design and run evals reflecting customer usage; produce analyses linking data to outcomes; run in-house fine-tuning or RL-style experiments when needed.
  • Collaborate effectively with large production teams: provide clear specs, fast feedback loops, and structured review processes; engage in improving outputs from annotation/creation efforts; not primarily responsible for hiring or people operations.

Qualifications

  • 4–5 years of experience building or improving deep learning systems where data quality mattered materially (training, post-training, evals, or agentic systems).
  • Strong intuition for data ingredients that drive model improvements: what to collect, filter, synthesize, and how to measure.
  • Ability to communicate clearly with researchers and engineers: turning research objectives into concrete specs, and messy outputs into actionable insights.
  • Extremely detail-oriented in diagnosing subtle data quality issues and failure modes.
  • Solid programming ability with a bias for shipping: Python proficiency required; Comfort with SQL/structured data workflows strongly preferred; For coding-focused work, proficiency in one or more major languages (e.g., C++, Java, Go, Rust, JS/TS) is a plus.
  • Comfort designing quality systems: rubrics, validation scripts, gold sets, sampling strategies; statistical checks and slice-based evaluation; human-in-the-loop review loops grounded in measurable criteria.

Skills

Required:PythonData quality assessmentTechnical communication
Nice to have:SQLProgramming languages (C++, Java, Go, Rust, JS/TS)
Last updated Sep 2, 2026. Interested? Apply on the company site.

About Training Superintelligence

Turing develops large-scale RL environments and data generation systems that train multimodal agents to improve model performance in coding, real-world, economically valuable tasks, and advanced STEM reasoning.

Train AIBuild AIHire AI TalentAI for BFSIEMNAIDatasetsEnterprise Knowledge WorkMultimodal
Company profileWebsite

More open roles at Training Superintelligence