Research Engineer

Aceolution; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Aceolution is seeking motivated Research Engineers and AI Research Scientists to contribute to next-generation AI evaluation frameworks and benchmarking systems. This role involves designing and executing AI experiments, building scalable Python-based tools, and working with Large Language Models to improve model performance.

You will collaborate with research and engineering teams, maintain reproducible code with Git, and document methodologies and findings to guide future AI development.

Qualifications

• Master's or PhD in CS/AI/ML or a related STEM field.
• Experience designing experiments, analyzing data, and validating model performance.
• Familiarity with Git, Jupyter/Colab, and modern IDEs.

Responsibilities

• Design, implement, and evaluate AI experiments to benchmark model performance.
• Develop AI evaluation frameworks and testing pipelines.
• Work with LLMs and ML models to analyze outputs and improve systems.
• Produce reproducible Python-based tooling for experiments.
• Document methodologies and findings with clear, technical recommendations.
• Collaborate with research, engineering, and cross-functional teams.

Skills

Python programming

Machine Learning

Deep Learning

LLMs

Git

Jupyter/Colab

Analytical thinking

Education

Master's or PhD in CS/AI/ML or related STEM

Tools

PyTorch

TensorFlow

Job description

Job Title: Research Engineer/AI Research Engineer

Hours - 35hours/Week

Job Summary:

We are seeking highly motivated Research Engineers and AI Research Scientists to contribute to the development of next-generation AI evaluation frameworks and benchmarking systems. This role is ideal for professionals with a strong research background who are passionate about advancing machine learning, large language models (LLMs), and AI experimentation.

As part of a cutting-edge AI research initiative, you will collaborate with multidisciplinary teams to design, implement, and evaluate robust AI systems that improve model performance, reliability, and safety.

Key Responsibilities

• Design, develop, and execute AI/ML experiments to evaluate model performance and behavior.
• Build and enhance AI evaluation frameworks, benchmarking methodologies, and testing pipelines.
• Work with Large Language Models (LLMs) and other machine learning models to analyze outputs and improve system quality.
• Develop scalable Python-based tools for data processing, experimentation, and analysis.
• Interpret experimental results and provide actionable insights based on quantitative and qualitative evaluations.
• Collaborate with research, engineering, and cross-functional teams to deliver high-quality AI solutions.
• Maintain clean, reproducible code using version control systems such as Git.
• Document methodologies, findings, and technical recommendations.

Required Qualifications

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Physics, Computational Sciences, or a related STEM discipline.
• Experience in one or more of the following roles:
• Research Engineer
• Applied Scientist
• Machine Learning Engineer
• Research Scientist
• AI Researcher
• Similar research-focused AI/ML positions
• Strong proficiency in Python programming.
• Hands-on experience with Machine Learning, Deep Learning, and Large Language Models (LLMs).
• Experience designing experiments, analyzing data, and validating model performance.
• Familiarity with Git, modern IDEs, and Jupyter Notebook or Google Colab environments.
• Excellent analytical thinking, problem-solving, and communication skills.

Preferred Qualifications

• Experience with AI evaluation, benchmarking, red teaming, or AI safety testing.
• Research publications in AI, Machine Learning, NLP, or related domains.
• Experience working with deep learning frameworks such as PyTorch or TensorFlow.
• Exposure to experimental research methodologies and reproducible AI workflows.