Platform Engineer, RL & Eval Data

🔥 1 hour ago

🇦🇷 Argentina – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 11%

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Anyone AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

📚 Education

🤖 Artificial Intelligence

🎯 Recruiter

💰 $1.5M Pre Seed Round - Anyone AI on 2022-06

Education • Artificial Intelligence • Recruitment

Anyone AI is a Latin America–focused career accelerator and training academy that develops software engineers into AI and machine learning professionals through intensive, remote, mentor-led programs. It combines technical coursework (e. g. , Machine Learning Developer track), professional preparation (resume/LinkedIn optimization, interview coaching, English practice), and a placement-oriented model (income-share payments and access to employer partnerships) to help graduates secure higher-paying AI roles globally. Anyone AI also operates a talent marketplace connecting its community to companies seeking AI talent.

📋 Description

• Maintain and improve existing evaluation, RL and annotation platforms in production • Fix bugs, reduce technical debt, improve test coverage and documentation • Design and ship new features across databases, backends, APIs and internal tools • Scale platforms to larger workloads with predictable performance and cost • Build RL environments and infrastructure including sandboxes, environment images, rollouts and reward computation • Implement monitoring, alerting, incident response, access control, secure handling of untrusted code and client-data protection • Build tooling used by task authors, reviewers and project leads • Help produce fast-turnaround samples for projects • Collaborate with task writers, data reviewers and AI labs to turn requirements into software

🎯 Requirements

• 5+ years in software, data or ML engineering, with recent work in AI/ML data, model evaluation, annotation or developer tooling • Strong backend engineering in Python • Experience designing and building APIs and data models • Experience with relational databases such as Postgres, including schema design, migrations and query performance • TypeScript and React skills sufficient to build and maintain internal tools • Experience designing distributed systems running many long-running jobs concurrently • Experience with job orchestration, workflow engines and queues, including retries, idempotency and failure recovery • Experience with Docker, Kubernetes or similar container orchestration and at least one major cloud provider • Experience with observability: logging, metrics, tracing and alerting • Knowledge of security fundamentals including secrets management, isolation and access control • Hands-on experience building RL environments for LLM agents • Experience running agent code in isolated sandboxes at scale • Experience building and caching environment images • Experience with high-throughput rollout collection • Experience feeding rollouts and rewards into RL post-training pipelines • Hands-on experience building or running LLM/LLM-agent evaluation harnesses or benchmarks • Experience writing verifiers, graders or reward functions • Understanding of frontier model evaluation concepts including pass rates, pass@k, headroom, discrimination and reward hacking • Experience with LLM provider APIs and tracking model cost and usage • Experience building annotation, labeling or human-data tooling • Experience with contributor and reviewer workflows, quality control and calibration • Fluent English • Ability to use AI coding agents carefully and review their output rigorously • Ability to thrive in ambiguity, work independently and take initiative • Clear written communication with engineers and non-engineers

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