Research Engineer, Frontier Data

Job not on LinkedIn

🔥 43 minutes ago

🌐 Brazil, Colombia – Remote

🇧🇷 Brazil – Remote 🇨🇴 Colombia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📚 Research Engineer

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Turing

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2018

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Turing is a leading company in the field of artificial intelligence, specializing in the advancement of AGI (Artificial General Intelligence) and the evaluation and training of large language models (LLMs). Turing offers a comprehensive range of AI solutions, including model performance assessments, multimodal capabilities integration, and custom engineering for enterprises looking to optimize their AI operations. The company bridges cutting-edge AI research with practical applications, empowering organizations to leverage advanced AI for various real-world challenges.

📋 Description

• Translate clients' evolving research goals into technical proposals and clear data requirements • Provide feasibility assessments, assumptions, acceptance criteria, and evaluation requirements • Create rubrics, counterexamples, and boundary cases • Audit produced data for subtle errors, reward hacking, leakage, ambiguity, inconsistent assumptions, and distribution shifts • Group failures and convert findings into production instructions and improvements • Design task suites, ground-truth signals, verifiers, unit tests, reward functions, validators, environment interfaces, APIs, tool schemas, state abstractions, and database schemas • Build project-specific verification systems combining deterministic checks, model-based evaluators, and human review • Implement automated validation and filtering, including deduplication, decontamination, leakage and consistency checks, and difficulty/diversity controls • Develop synthetic-data generation and augmentation pipelines • Create dataset documentation and data cards • Design and run evaluations reflecting client usage • Analyze pre/post comparisons, error breakdowns, and ablations to connect data with model outcomes • Run fine-tuning or RL-style experiments when needed to demonstrate measurable model improvement • Provide technical direction to distributed expert data-production networks • Own technical translation, acceptance criteria, evaluator/verifier design, quality diagnosis, and technical release recommendations • Communicate technical findings, quality risks, and recovery options directly to clients • Work primarily with a single frontier AI lab client while supporting other accounts as needed

🎯 Requirements

• 4–5 years of experience building or improving deep learning systems where data quality mattered materially • Strong intuition for data collection, filtering, synthesis, and measurement for model improvement • Ability to communicate research objectives as concrete technical specifications and outputs as actionable insights • Comfortable serving as the direct technical client point of contact • Extremely detail-oriented diagnosis of subtle data-quality issues and failure modes • Python proficiency required • Comfort with SQL/structured data workflows strongly preferred • For coding-focused work, proficiency in a major language such as C++, Java, Go, Rust, or JS/TS is a plus • Experience designing rubrics, validation scripts, gold sets, sampling strategies, statistical checks, slice-based evaluation, and human-in-the-loop review loops • RL or post-training experience is a strong plus, including RLHF/RLAIF, verifier training, reward modeling, RL fine-tuning, or environment design • Agentic evaluation experience is a strong plus • Multimodal expertise is a strong plus • STEM depth in math, physics, or engineering is a strong plus • Modern embodied AI/VLM-driven agent experience is a strong plus • Systems-thinking ability to simulate application APIs/data schemas and design realistic tasks • Direct frontier AI lab experience is not required

🏖️ Benefits

• Work directly with a frontier AI lab at the cutting edge of post-training and RL environment design • High autonomy and fast iteration • Talent-dense team with a rapid learning curve • Opportunity to showcase work at top conferences such as ICLR, ICML, and NeurIPS • Collaborate with and learn from exceptional colleagues with deep AI experience • Startup-speed environment with ownership and impact • Equal opportunity, diverse, inclusive, and authentic workplace

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