RL Deep Learning Engineer
$210k - $250kRecruiting from Scratch
Who is Recruiting from Scratch: Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire. RL Deep Learning Engineer Location: New York, NY (On-site)
Company Stage of Funding: Early-stage / Seed-backed
Office Type: On-site
Salary: $210,000 - $250,000 + Equity (0-0.4%)
Visa: No sponsorship available
Company Description Our client is building the foundational legal data infrastructure powering the next generation of AI systems. Their platform processes and structures millions of U.S. court records and legal filings, serving as the legal data layer for AI labs, legal AI startups, and enterprise legal workflows. The company already powers legal reasoning workflows for hundreds of law firms and multiple large-scale AI organizations. This is an opportunity to join a highly technical early-stage team building RL environments, evaluation harnesses, and benchmark systems for long-horizon legal reasoning tasks - infrastructure that will directly shape how future legal AI models are trained and evaluated. The role sits at the intersection of reinforcement learning infrastructure, evaluation systems, data pipelines, and large-scale document processing.
What You Will Do Build and maintain RL environment infrastructure for long-horizon legal reasoning tasks Design scalable evaluation harnesses, task runners, scoring systems, and sandboxed execution environments Build systems that convert raw legal filings and court records into benchmark and RL training tasks Develop contamination-free evaluation pipelines for frontier AI model testing Integrate with partner model APIs and evaluation harnesses Collaborate with attorneys and domain experts to translate legal workflows into structured evaluation tasks Work with messy, large-scale, real-world document datasets including PDFs and long-form legal filings Build scalable data pipelines for legal reasoning environments Develop tools for search, retrieval, reasoning, and drafting evaluations Write production-quality Python systems with strong engineering rigor Contribute to infrastructure supporting thousands of concurrent agent evaluations Leverage AI coding tools such as Cursor, Claude Code, and Codex in daily workflows Collaborate closely with engineers, attorneys, and AI partners Operate with high ownership in a lean, fast-moving engineering environment Take full ownership of systems from 0 → 1
Ideal Candidate Background 3-8 years of software engineering experience Strong Python engineering fundamentals Experience building production systems with high ownership Experience building systems from 0 → 1 Comfortable working with large-scale document or data processing systems Strong backend and infrastructure engineering intuition Experience working in high-signal startup or engineering environments Strong product ownership mindset Comfortable operating as a highly autonomous IC Experience with AI coding tools in daily workflow Strong debugging and systems thinking ability Comfortable working with ambiguous and evolving requirements Strong written and verbal communication skills Ability to move quickly while maintaining engineering quality Comfortable working onsite in NYC
Strong Signals Founding engineer or startup founder experience with demonstrated traction Experience building evaluation systems or benchmarking infrastructure Experience with RL environments or agent evaluation systems Experience with LLM evaluations or AI evaluation frameworks Experience with modern AI tooling and workflows Experience building scalable Python backend systems Experience with large-scale data or document pipelines TypeScript experience Experience working with messy real-world datasets Strong engineering ownership and initiative Experience collaborating with highly technical teams High agency and startup intensity tolerance Evidence of rapid career growth or exceptional ownership Strong systems design and infrastructure intuition
Compensation and Benefits Base salary: $210,000 - $250,000 Equity package up to 0.4% Direct ownership over core AI infrastructure systems High-impact role at an early-stage AI infrastructure company Work directly with frontier AI labs and legal domain experts Lean, highly technical engineering team Exposure to RL systems, evaluation harnesses, and large-scale AI infrastructure Fast-growing company with strong commercial traction Opportunity to shape the future of legal AI evaluation systems
Why Join This is an opportunity to build foundational RL infrastructure and evaluation systems for frontier legal AI. You'll work on difficult, high-leverage engineering problems involving long-horizon reasoning, document intelligence, scalable evaluation environments, and AI benchmarking systems. If you want deep technical ownership, exposure to frontier AI infrastructure, and the opportunity to help define how future AI systems are evaluated and trained, this role offers exceptional scope and leverage.
Company Stage of Funding: Early-stage / Seed-backed
Office Type: On-site
Salary: $210,000 - $250,000 + Equity (0-0.4%)
Visa: No sponsorship available
Company Description Our client is building the foundational legal data infrastructure powering the next generation of AI systems. Their platform processes and structures millions of U.S. court records and legal filings, serving as the legal data layer for AI labs, legal AI startups, and enterprise legal workflows. The company already powers legal reasoning workflows for hundreds of law firms and multiple large-scale AI organizations. This is an opportunity to join a highly technical early-stage team building RL environments, evaluation harnesses, and benchmark systems for long-horizon legal reasoning tasks - infrastructure that will directly shape how future legal AI models are trained and evaluated. The role sits at the intersection of reinforcement learning infrastructure, evaluation systems, data pipelines, and large-scale document processing.
What You Will Do Build and maintain RL environment infrastructure for long-horizon legal reasoning tasks Design scalable evaluation harnesses, task runners, scoring systems, and sandboxed execution environments Build systems that convert raw legal filings and court records into benchmark and RL training tasks Develop contamination-free evaluation pipelines for frontier AI model testing Integrate with partner model APIs and evaluation harnesses Collaborate with attorneys and domain experts to translate legal workflows into structured evaluation tasks Work with messy, large-scale, real-world document datasets including PDFs and long-form legal filings Build scalable data pipelines for legal reasoning environments Develop tools for search, retrieval, reasoning, and drafting evaluations Write production-quality Python systems with strong engineering rigor Contribute to infrastructure supporting thousands of concurrent agent evaluations Leverage AI coding tools such as Cursor, Claude Code, and Codex in daily workflows Collaborate closely with engineers, attorneys, and AI partners Operate with high ownership in a lean, fast-moving engineering environment Take full ownership of systems from 0 → 1
Ideal Candidate Background 3-8 years of software engineering experience Strong Python engineering fundamentals Experience building production systems with high ownership Experience building systems from 0 → 1 Comfortable working with large-scale document or data processing systems Strong backend and infrastructure engineering intuition Experience working in high-signal startup or engineering environments Strong product ownership mindset Comfortable operating as a highly autonomous IC Experience with AI coding tools in daily workflow Strong debugging and systems thinking ability Comfortable working with ambiguous and evolving requirements Strong written and verbal communication skills Ability to move quickly while maintaining engineering quality Comfortable working onsite in NYC
Strong Signals Founding engineer or startup founder experience with demonstrated traction Experience building evaluation systems or benchmarking infrastructure Experience with RL environments or agent evaluation systems Experience with LLM evaluations or AI evaluation frameworks Experience with modern AI tooling and workflows Experience building scalable Python backend systems Experience with large-scale data or document pipelines TypeScript experience Experience working with messy real-world datasets Strong engineering ownership and initiative Experience collaborating with highly technical teams High agency and startup intensity tolerance Evidence of rapid career growth or exceptional ownership Strong systems design and infrastructure intuition
Compensation and Benefits Base salary: $210,000 - $250,000 Equity package up to 0.4% Direct ownership over core AI infrastructure systems High-impact role at an early-stage AI infrastructure company Work directly with frontier AI labs and legal domain experts Lean, highly technical engineering team Exposure to RL systems, evaluation harnesses, and large-scale AI infrastructure Fast-growing company with strong commercial traction Opportunity to shape the future of legal AI evaluation systems
Why Join This is an opportunity to build foundational RL infrastructure and evaluation systems for frontier legal AI. You'll work on difficult, high-leverage engineering problems involving long-horizon reasoning, document intelligence, scalable evaluation environments, and AI benchmarking systems. If you want deep technical ownership, exposure to frontier AI infrastructure, and the opportunity to help define how future AI systems are evaluated and trained, this role offers exceptional scope and leverage.
Vacancy posted 1 day ago
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