Research Engineers, Post-Training
$150k - $250k • San Francisco • FullTime
Posted 3mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Distyl AI is seeking Research Engineers to bridge the gap between frontier AI research and production systems that deliver tangible business value. This role is ideal for engineers passionate about designing AI systems, rapidly prototyping new concepts, and transforming promising ideas into reliable, production-ready systems for real-world customer environments. Research Engineers will operate at the intersection of applied research, systems engineering, and customer deployment, designing and implementing compound AI systems, conducting experiments, building evaluation frameworks, and collaborating with AI Researchers, AI Engineers, and customer stakeholders. The focus is on turning new techniques into robust, measurable, and operable systems within production settings.
Responsibilities
- Design and execute post-training workflows to enhance AI system behavior, reliability, and usefulness.
- Develop datasets, preference signals, evaluation suites, reward models, fine-tuning workflows, and feedback loops for applied AI use cases.
- Investigate the impact of various post-training techniques on system behavior across enterprise workflows and production constraints.
- Build infrastructure for experimentation, model comparison, regression testing, and behavior analysis.
- Collaborate with AI Researchers on new post-training methods and with AI Engineers on applying successful techniques in deployed systems.
- Analyze model outputs, failure modes, human feedback, and production traces to identify areas for behavioral improvement.
- Create repeatable processes for adapting AI systems to customer domains while maintaining robustness, transparency, and maintainability.
- Communicate model behavior, evaluation results, limitations, and tradeoffs clearly to internal teams and customer stakeholders.
Requirements
- Experience with fine-tuning, preference optimization, reinforcement learning, reward modeling, synthetic data, evals, or related post-training techniques.
- Strong programming and experimentation skills, including building training and evaluation pipelines, running controlled experiments, analyzing results, and iterating quickly.
- A research-oriented mindset focused on understanding the 'why' behind behavior changes, not just benchmark improvements.
- An AI systems mindset, understanding that model behavior is influenced by data, prompts, tools, retrieval, evaluators, and deployment context.
- An AI-native working style, utilizing AI tools daily to accelerate coding, analysis, debugging, experimentation, and research.
- A bias towards measurement, quantifying behavioral improvements through evaluations, comparisons, regression tests, and production-relevant metrics.
- Comfort balancing research ambition with practical constraints like cost, latency, reliability, data availability, and customer requirements.
- An ownership mentality, taking responsibility for real system outcome improvements from post-training work, not just offline scores.
Benefits
- Base salary range of $150K – $250K, depending on experience, location, and level.
- Meaningful equity.
- Comprehensive benefits package.
- 100% coverage of medical, dental, and vision insurance for employee and dependents.
- Flexible time off.
- Retirement and financial planning benefits (HSA, FSA, commuter accounts, 401(k), financial coaching).
- Comprehensive wellness benefits (physical fitness, mental well-being, fertility and family-building benefits).
- Complimentary in-office lunches and snacks.
- Access to state-of-the-art AI models and modern AI tools.
- Ownership of high-impact projects across top enterprises.