About the role
About Distyl AI
Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.
We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.
What We Are Looking For
At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.
Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org.
Key Responsibilities
The Post-Training team focuses on adapting foundation models to real-world performance and alignment requirements. Researchers develop and evaluate techniques such as supervised fine-tuning, preference optimization (DPO, RLHF, RLAIF), and continual adaptation to align models with Distyl’s enterprise systems. The goal is to bridge raw model capability with trustworthy, contextually aligned system behavior
Researchers in Post-Training investigate new methods for aligning large models with human and system-level objectives. They explore trade-offs between generalization and specialization, data efficiency and robustness, capability and controllability. Their work informs how Distyl leverages foundation models safely, effectively, and at scale across industries
What We Require
Deep Understanding of Post-training Techniques: Familiarity with supervised fine-tuning, preference optimization (RLHF/DPO), LoRA/PEFT, and instruction-tuning pipelines.
Experience Adapting Frontier Models: You’ve tuned or adapted LLMs/SLMs to specialized domains or behaviors through data curation, reward modeling, or continual pretraining.
Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.).
Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.
Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.
Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.
Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize.
What We Offer
The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
100% covered medical, dental, and vision for employees and dependents
401(k) with additional perks (e.g., commuter benefits, in‑office lunch)
Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems
Ownership of high‑impact projects across top enterprises
A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence
Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.
#LI-Hybrid
We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Aplyr's read
Distyl AI is at the forefront of AI-driven content and data solutions, attracting a diverse team of specialists in AI systems and strategic growth.
What's promising
- •Distyl AI offers innovative AI-driven solutions for content generation and data analysis.
- •The company is expanding rapidly, hiring across diverse roles in AI and strategic growth.
- •Distyl AI's focus on healthcare solutions indicates a commitment to impactful industry applications.
What to watch
- •Limited public information about company culture and work-life balance.
- •High specialization in AI roles may limit opportunities for non-technical applicants.
- •Potential challenges in maintaining innovation pace in a competitive AI market.
Why Distyl AI
- •Distyl AI specializes in AI systems for both content generation and data analysis.
- •The company hires for niche roles like AI Strategist and Forward Deployed Architect.
- •Focus on healthcare solutions differentiates Distyl AI in the AI landscape.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Distyl AI
Distyl AI is a technology company specializing in AI-driven solutions for content generation and data analysis.
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