Machine Learning Research Intern

Worlds builds operational AI for the physical world. Our platform connects real-time camera feeds to production-grade computer vision models, enabling clients across logistics, aviation, and industrial operations to automate decisions at scale. We train custom detection, tracking, and search models on client-specific environments and deploy them live across multi-camera setups on cloud infrastructure.

The Role

*** YOU MUST BE A TEXAS BASED RESIDENT TO APPLY FOR THIS ROLE***

We are looking for a motivated ML Research Intern to join our team for Summer 2026 (3 months, remote). Working closely with our forward research team, you will help explore and shape emerging research directions that will define the next evolution of our platform.

These are forward-looking areas — part of your role will be to help scope what is worth pursuing and how it connects to real operational problems we see across our clients.

Research Areas

Agentic AI

Programming Proficiency: Strong experience in programming languages such as Python, Java, or JavaScript

Pattern-of-Life Modeling

Research how behavioral patterns of people, vehicles, and assets can be modeled over time to enable richer search, retrieval, and anomaly detection — for example, understanding what is normal for a given environment and surfacing meaningful deviations.

Graph-Based Reasoning

Investigate how relationships between objects, events, and environments can be represented as graph structures to enable more expressive querying and inference across complex operational scenes.

Behavioral Analysis

Develop approaches to detect, classify, and interpret behavioral signals from continuous video streams — moving from object-level detection toward understanding what is actually happening in a scene over time.

What You’ll Do

• Explore and synthesize cutting-edge research across your area of interest and assess applicability to real-world operational AI

• Collaborate with the research and engineering team to understand problem space and contribute meaningful research thinking

• Develop and test hypotheses, run experiments, and iterate on ideas in a fast-moving environment

• Communicate findings clearly through written summaries and discussions with the team

• Help define what directions are worth pursuing and contribute to shaping the research roadmap

What We’re Looking For

Required

• Currently pursuing an MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field

• Solid foundations in machine learning — comfortable with training, evaluation, and debugging models in code, not just theory

• Hands-on experience with LLM fine-tuning or working with large pre-trained models (e.g. Mistral, Gemma, LLaMA, or similar)

• Strong Python skills — you write clean, reproducible ML code, not just research scripts

• Familiarity with statistical thinking around model evaluation — confidence intervals, significance, metric design

• Comfortable working with ambiguity and defining problem structure, not just executing defined tasks

Nice to Have

• Experience with computer vision models or detection pipelines (YOLO, RT-DETR, or similar)

• Familiarity with semantic search, embeddings, or retrieval systems (CLIP, Qdrant, FAISS)

• Exposure to MLOps tooling (MLflow, ZenML, Metaflow, or similar)

• Experience with VLMs (LLaVA, MoLMo, Gemma Vision, or similar)

• Prior industry internship experience in an applied ML or research engineering role

Internship Details

Duration: 3 months — Summer 2026

Format: Remote

Compensation: $30/hr

Team: Forward Research Team & visibility to Leadership Team

How to apply.

If you are interested in applying for a position with Worlds, please fill out this form and send your resume and cover letter to careers@worlds.io