Software Engineer – AI Research Engineering

Role Overview

Software Engineer – AI Research Engineering (Contract) Join a leading AI research organization to help build frontier AI models. You’ll work at the intersection of machine learning research, multimodal AI, and large-scale data infrastructure, including onboarding open-source foundation models, implementing state-of-the-art research, and building scalable data curation pipelines to accelerate training.

Responsibilities

• Productionize state-of-the-art open-source ML research and foundation models
• Build scalable data curation/preprocessing pipelines for frontier model training
• Develop high-performance Python applications for large-scale dataset processing
• Design and optimize SQL workflows for data preparation and analytics
• Build robust ML infrastructure for experimentation, evaluation, and deployment
• Optimize GPU utilization, memory management, and PyTorch training pipelines
• Troubleshoot complex ML infrastructure issues, including CUDA and performance bottlenecks
• Collaborate with research scientists and engineering teams to accelerate AI research
• Write clean, maintainable, well-documented production-quality code
• Participate in code reviews and contribute to engineering best practices

Requirements (Must-Have)

• Master’s or Ph.D. in CS/AI/ML/Computer Vision/NLP or related field
• 6+ years experience in Research Engineering, ML Engineering, or Software Engineering with significant ML implementation
• Strong programming in Python, PyTorch, and SQL
• Experience implementing/reproducing cutting-edge ML research from papers
• Experience with ML infrastructure, backend systems, or distributed ML pipelines
• Strong understanding of GPU computing, CUDA, memory optimization, and performance debugging
• Experience with large-scale datasets and distributed data processing pipelines
• Research experience in one or more:
  • Computer Vision
  • LLMs
  • Multimodal AI (video, audio, vision-language models)
• Experience onboarding/adapting open-source foundation models for research or production
• Ability to work independently and collaborate effectively across research and engineering teams
• Strong communication, problem-solving, and technical documentation

Preferred Qualifications

• Ph.D. with published research in ML/CV/NLP/multimodal AI
• Publications/presentations at major conferences (CVPR, ICCV, ECCV, ACL, EMNLP, NeurIPS, ICML, ICLR)
• Experience at top AI labs, major tech companies, or university research organizations
• Experience implementing open-source research papers into production systems
• Experience building/supporting ML infrastructure at scale
• Familiarity with AWS, Azure, or GCP
• Experience with Linux, shell scripting, distributed computing
• Knowledge of modern MLOps and model deployment