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Applied AI Researcher, Post-Training

DistylSan Francisco, CA

$150,000 - $250,000 / year

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Overview

Schedule
Full-time
Career level
Senior-level
Remote
Hybrid remote
Compensation
$150,000-$250,000/year
Benefits
Career Development
Retirement Savings
Dental Insurance

Job Description

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.

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FAQs About Applied AI Researcher, Post-Training Jobs at Distyl

What is the work location for this position at Distyl?
This job at Distyl is located in San Francisco, CA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Distyl?
Candidates can expect a pay range of $150,000 and $250,000 per year.
What employment applies to this position at Distyl?
Distyl lists this role as a Full-time position.
What experience level is required for this role at Distyl?
Distyl is looking for a candidate with "Senior-level" experience level.
What benefits are offered by Distyl for this role?
Distyl offers following benefits: Career Development, Retirement Savings, Dental Insurance, Health Insurance, and Vision Insurance for this position. Actual benefits may vary depending on the employer's policies and employment terms.
What is the process to apply for this position at Distyl?
You can apply for this role at Distyl either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.