AI​/ML Engineer

Company Description

Trendline Labs is at the forefront of data analytics innovation for betting markets, including sports and prediction markets, by equipping users with AI-driven intelligence for smarter decision-making. With a foundation in sports data expertise, the company transforms complex raw information such as referee trends, market sentiment, and player stats into actionable insights. Through advanced products like Trendline and Optimus, the company unifies fragmented data systems, enabling real-time queries and optimized opportunities across global markets.

As betting converges further with financial trading, Trendline Labs is leading the charge in developing the AI technologies driving future industry advancements. Be part of our mission to redefine betting intelligence.

This is a full-time remote/ hybrid role for an AI/ML Engineer. While remote willingness to relocate to the Atlanta area will be considered. The AI/ML Engineer will focus on designing, building, and deploying machine learning models and algorithms for use in our cutting-edge betting intelligence platforms. Responsibilities include building LLMs that interact with real-time feeds, conducting performance optimization for machine learning solutions, architecting real-time data pipelines to stream, store, and analyze high-frequency market data.

You will also be developing agents for sentiment scraping across web based platforms such as X and Reddit.

• Background in vector search
  , retrieval-augmented systems
  , or LLM tool orchestration
  .
• Strong background in machine learning
  , neural networks
  , and pattern recognition
  .
• Proficiency in Python and/or Go
  , with understanding of production ML engineering.
• Experience with ML frameworks such as Py Torch ,
  Tensor Flow
  , or JAX
  .
• Strong understanding of probability
  , statistics
  , and time-series modeling
  .
• Ability to design, tune, and deploy models in real-time environments.
• Experience with high-volume data systems (streaming, batch ETL, or real-time ingestion).
• Familiarity with modern AI tools, frameworks, and libraries.
• Experience with distributed computing or cloud-based ML deployment is a plus.
• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field is highly desirable.
• Ability to work collaboratively in a hybrid team environment.