Staff Research Engineer – Frontier AI, RL & Evaluation

HumanitApp; San Francisco (CA); Hybrid; USD 110,000 - 193,000; Full time

Job summary

Turing in San Francisco, CA is seeking a Staff Research Engineer to advance frontier AI systems through data, algorithms, and evaluation tooling. This is a contract position focused on research-to-implementation, with close collaboration across Research, Engineering, Product, and Operations teams.

You will design and run rigorous experiments, build prototypes, and contribute to data generation, reinforcement learning, and model understanding. Duration: 3 months; 8 hours/day with PST overlap.

Qualifications

• PhD or MS in AI/ML/CS or related field.
• Minimum 7+ years of professional experience in ML research engineering.
• Strong foundations in ML and experience designing experiments, training models, evaluating models.

Responsibilities

• Conduct research on frontier AI systems.
• Build research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks.
• Train, test, and evaluate models using modern ML tools.
• Analyze results and draw evidence-based conclusions.
• Collaborate with Research, Engineering, Product, and Operations teams.

Skills

Python

Experiment design

Research leadership

Communication

Machine learning

ML pipelines

Education

PhD or MS in Artificial Intelligence, ML, CS, or related field

Tools

TensorFlow / PyTorch

Job description

Future projects, not immediate vacancies. Check each network's country and experience requirements.

Turing builds large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. Our environments evaluate and improve AI models on complex, long-range, multi-step workflows across high-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, and Customer Experience.

Official job description checked 2026-10-24:

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L

About the Role

Turing builds large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. Our environments evaluate and improve AI models on complex, long-range, multi-step workflows across high-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, and Customer Experience.

Software engineering environments for coding agents

MCP-based environments for function-calling agents across enterprise and consumer applications

We are looking for Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training.

This role sits at the intersection of research and engineering. You will investigate high-impact questions, design rigorous experiments, build research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications.

You will contribute to areas including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

What You’ll Do

Conduct Research on Frontier AI Systems

Investigate the capabilities, limitations, and training methods of frontier AI systems.

Formulate research questions that inform Turing’s products, platforms, and technical strategy.

Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

Stay current with advances in machine learning and identify opportunities for meaningful technical contributions.

Build and Evaluate Research Systems

Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks.

Train, test, and evaluate models using modern AI and machine learning tools.

Analyze experimental results and draw clear, evidence-based conclusions.

Establish strong practices for experimental rigor, data quality, reproducibility, and interpretation.

Iterate quickly from initial hypotheses to validated technical insights.

Translate Research into Practical Impact

Collaborate with Research, Engineering, Product, and Operations teams.

Translate research findings into improvements for Turing’s products, platforms, and AI capabilities.

Identify which ideas are ready to move from exploration into scalable, real-world applications.

Communicate technical findings clearly to both specialized and cross-functional audiences.

Contribute to the Research Community

Share findings through technical reports, publications, open-source work, workshops, or conferences where appropriate.

Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration.

Represent Turing thoughtfully within the broader AI research community.

What We’re Looking For

PhD or Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field. Exceptional equivalent research experience will also be considered.

Minimum 7+ years of professional experience with significant research engineering experience working on machine learning or frontier AI systems.

Strong foundations in machine learning and practical experience designing experiments, training models, evaluating models, or developing AI systems.

Demonstrated research experience in one or more of the following areas:Synthetic or agentic data generation

Reinforcement learning or post-training

AI evaluation

AI agents or tool-using systems

Strong programming skills, particularly in Python, with the ability to implement, test, and iterate quickly in a research environment.

Experience with modern AI and machine learning frameworks and tooling.

Strong scientific judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making.

Excellent written and verbal communication skills.

Ability to work independently and collaborate effectively across research and engineering teams.

Experience mentoring engineers or researchers and providing technical leadership.

Commitments Required: 8 hours per day with at least 4 hour overlap with PST.

Employment Type: Contractor position (Note: this role does not include medical/paid leave).

Duration of Contract: 3 months [expected start date is next week].

Evaluation Process :

AI Interview (~20 mins)

Delivery interview (~45 mins)

Confirm current eligibility, workload and final terms with Turing. Referral rewards are separate from applicant compensation.

QA

Compensation context

Compensation is not stated in the current feed. Confirm the rate and workload before accepting an assessment or project.

• Ability to work independently and collaborate effectively across research and engineering teams.