Data & ML Researcher

Soledad Data Solutions; California, Northern (MO, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Mylitm is seeking a Data & ML Researcher who sits at the intersection of research and engineering to advance autonomous decisioning in high-stakes domains. You will design rigorous experiments, translate results into production prototypes, and collaborate with MLOps to deploy.

You will work with modern ML techniques including LLMs, reinforcement learning, and structured prediction, shaping the research roadmap for one or more product surfaces and publishing internal notes when appropriate.

Qualifications

• PhD or equivalent in ML, statistics, or a related quantitative field.
• Strong publication record or evidence of shipped applied-research work.
• Fluent in PyTorch or JAX; comfortable with distributed training.
• Strong software engineering fundamentals — you can take a notebook to a service.

Responsibilities

• Design and run rigorous experiments on candidate model architectures and decisioning algorithms.
• Translate findings into production-grade prototypes and partner with MLOps to deploy.
• Read, summarize, and reproduce relevant academic and industry research.
• Build evaluation harnesses, eval datasets, and metrics that reflect real customer outcomes.
• Publish internal research notes and contribute to external publications when appropriate.

Skills

Strong publication record

Technical writing

De-risking ideas with experiments

Education

PhD or equivalent in ML/related field

Tools

PyTorch

JAX

Distributed training

Job description

Autonomous Decisioning Research & Engineering

Data & ML Researcher

About this role

You will work at the intersection of research and applied engineering, exploring how modern ML — including LLMs, reinforcement learning, and structured prediction — can power autonomous decisioning in high-stakes domains. You will own the research roadmap for one or more product surfaces, shape the experimental infrastructure, and partner with engineering to ship.

What you will do

• Design and run rigorous experiments on candidate model architectures and decisioning algorithms.
• Translate findings into production-grade prototypes and partner with MLOps to deploy.
• Read, summarize, and reproduce relevant academic and industry research.
• Build evaluation harnesses, eval datasets, and metrics that reflect real customer outcomes.
• Publish internal research notes and contribute to external publications when appropriate.

What we are looking for

• PhD or equivalent industry experience in ML, statistics, or a related quantitative field.
• Strong publication record or evidence of shipped applied-research work.
• Fluent in PyTorch or JAX; comfortable with distributed training.
• Strong software engineering fundamentals — you can take a notebook to a service.
• Clear technical writing and a habit of de-risking ideas with simple experiments first.

Nice to have

• Experience with autonomous decisioning, Bayesian inference, or causal inference.
• Hands-on experience deploying LLM-powered agents or tool-use systems.