Engineer ML + Agent Design
Offer summary
Qualifications:
At least 3 years of experience with machine learning systems, including data pipelines and training frameworks., Strong expertise in large language models (LLMs), prompting, fine-tuning, and ML experimentation., Knowledge of retrieval systems, vector databases, and reasoning techniques for large-scale text data., Ability to blend research and engineering to enhance agent capabilities and thrive in fast-paced environments..Key responsibilities:
- Develop and improve ML pipelines for agent behaviors using advanced techniques.
- Prototype and experiment with novel agent reasoning, planning, and tool usage for complex domains.
- Conduct structured experiments to evaluate and optimize agent performance, translating findings into production solutions.
- Collaborate with infrastructure teams to ensure robustness, scalability, and reliability of agent models in production.
Job description
About ChestnutChestnut is building the first AInative operating system for insurance distribution by transforming how the $1T+ insurance industry allocates its largest spend: sales and distribution.
Backed by a16z, we’re replacing legacy systems with a modern, flexible platform that helps carriers automate complex workflows, optimize every distribution dollar, and unlock new growth. We have major insurers under contract, and early adopters are expanding.
This is a generational platform shift. Recent advances in agentic AI make it possible to automate what was once manual and errorprone. We’ve spent years building the data model and context layer required to make this real, and now we’re scaling with urgency.
At Chestnut, we operate with the belief that small, highcontext teams working with bestinclass tools and colleagues can achieve outsized results. We embody what it means to be AIlean: chasing 10x productivity gains that allow us to scale impact beyond our headcount.
If you’re excited to modernize the infrastructure of one of America’s most essential industries, we’d love to meet you. Whether shaping core product experiences or laying the groundwork for intelligent automation, your work will accelerate a onceinageneration transformation.
Engineering at Chestnut
We’re building the modern infrastructure for AIdriven insurance operations. That means wellstructured data models, realtime event pipelines, clean APIs, and usable tools that support humans and agents working in parallel.
What Youll DoDevelop and refine ML pipelines for agent behaviors using prompting, finetuning, retrievalaugmented generation, and reinforcement learning techniques.
Prototype and experiment with novel agent reasoning, multistep planning, and tool usage for complex, dataheavy domains.
Run structured experiments to evaluate agent performance, optimize reasoning and retrieval, and translate findings into productionready solutions.
Build data pipelines and evaluation frameworks that support rapid iteration and deployment of new agent capabilities.
Collaborate with orchestration and infra teams to ensure agent models are robust, scalable, and reliable in production.
You Might Be a Fit If You…Have 3+ years of experience building and analyzing ML systems, including data pipelines, and training frameworks.
Have strong experience with LLMs, prompting, finetuning, and ML experimentation.
Understand retrieval systems, vector databases, and reasoning techniques for largescale text datasets.
Enjoy blending research and engineering to push agent capabilities forward.
Thrive in fastpaced environments where prototypes quickly evolve into production systems.
BenefitsCompetitive salary and equity, with 10 year exercise window for stock options
Remotefirst culture built on trust, autonomy, and high performance
Team offsites for all of us to bond
Take what you need vacation policy
Top notch health, dental, and vision insurance subsidized by us
Develop and refine ML pipelines for agent behaviors using prompting, finetuning, retrievalaugmented generation, and reinforcement learning techniques.
Prototype and experiment with novel agent reasoning, multistep planning, and tool usage for complex, dataheavy domains.
Run structured experiments to evaluate agent performance, optimize reasoning and retrieval, and translate findings into productionready solutions.
Build data pipelines and evaluation frameworks that support rapid iteration and deployment of new agent capabilities.
Collaborate with orchestration and infra teams to ensure agent models are robust, scalable, and reliable in production.
Have 3+ years of experience building and analyzing ML systems, including data pipelines, and training frameworks.
Have strong experience with LLMs, prompting, finetuning, and ML experimentation.
Understand retrieval systems, vector databases, and reasoning techniques for largescale text datasets.
Enjoy blending research and engineering to push agent capabilities forward.
Thrive in fastpaced environments where prototypes quickly evolve into production systems.
Competitive salary and equity, with 10 year exercise window for stock options
Remotefirst culture built on trust, autonomy, and high performance
Team offsites for all of us to bond
Take what you need vacation policy
Top notch health, dental, and vision insurance subsidized by us
Benefits
You Might Be a Fit If You…
Required profile
Experience
Other Skills
- Deductive Reasoning
- Collaboration
- Adaptability
- Problem Solving
Related jobs
Siemens
- From: Edmonton (Full Remote)
- Full time
X2O Media
- From: United States, Trotwood (Full Remote)
- Full time
Abbott
- From: New York (USA), Rochester, Buffalo (Full Remote)
- Full time
NEORIS
- From: Spain (Full Remote)
- Full time
Motive
- From: United States (Full Remote)
- Full time