Machine Learning Analyst | 100% Remoto | LATAM
What do we offer?
Prometeo Talent is a recruitment agency with a strong presence across the Americas and Europe.
We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.
We have partnered with a U.S.-based company specialized in marketing effectiveness measurement.
They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.
We are looking for a Data Analyst (Machine Learning) to join our client's global team.
This role is ideal for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.
The idóneo candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English.
The position is open to a range of experience levels, from recent graduates with cit user signals into post‐training.Collaborate with tooling,



product, and training teams to improve the usefulness, reliability, and agentic capabilities of frontier models.Closely liaise with research, engineering and cross‐functional teams to determine which integrations are production‐ready for inclusion in major model releases.Degree in Computer Science, Machine Learning, or a related field; advanced degree (MS/PhD) preferred with a strong publication record in top‐tier AI conferences.Experience with multimodal post‐training workflows and data pipelines, particularly for agentic systems and tool use.Hands‐on experience applying post‐training at scale using distributed training frameworks (e.g., multi‐node GPU environments).
Demonstrated experience improving model capabilities in areas such as reasoning, tool use, and multi‐agent coordination that achieve SOTA results.Proven track record of open‐source contributions related to agentic systems or tool use (code, datasets, or models) on platforms such as GitHub or Hugging Face.Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV).
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📌 Machine Learning Engineer – Ml Evaluation & Experiment Design (Santa Fe)
🏢 YO AI Labs
📍 Santa Fe