PhD ML Research Engineer - Deep Learning & Vision

Optimal; Warren (MI); On-site; USD 120,000 - 180,000; Full time

Job summary

Optimal is seeking a Machine Learning Research Engineer with a PhD or near completion, to advance ML/DL research and develop production-ready AI systems. The role emphasizes applying ML, computer vision, and scientific computing to real-world engineering problems, with collaboration across research and engineering teams.

The ideal candidate will design and optimize models, manage end-to-end ML workflows, and contribute to cutting-edge AI research while translating concepts into scalable

Qualifications

• PhD or near completion in ML/AI/CI fields from a reputable university.
• Strong publication record or research contributions in ML/AI.
• Expertise with Python and C++, and ML frameworks (PyTorch, TensorFlow).
• Experience turning research ideas into production-grade AI systems.
• Strong mathematical foundation in linear algebra, statistics, and optimization.
• Experience with Linux, Git, Docker, and modern workflows.

Responsibilities

• Design, develop, train, and optimize ML/DL models for real-world tasks.
• Own the complete ML lifecycle from data collection to deployment.
• Develop architectures including CNNs, LSTMs, GNNs, RL, and Transformers.
• Conduct experiments, evaluate performance, and push algorithmic improvements.
• Work with large-scale datasets and coordinate with cross-functional teams.
• Translate research concepts into scalable, production-ready AI systems.
• Document methodologies and results; contribute to AI research initiatives.

Skills

Python

C++

PyTorch

TensorFlow

Keras

Scikit-learn

Deep Learning

Computer Vision

Reinforcement Learning

Graph Neural Networks

Education

PhD in ML/AI/CS/Engineering

Tools

Docker

Git

Linux

CUDA

Job description

Optimal is seeking a Machine Learning Research Engineer with a PhD or near completion, to advance ML/DL research and develop production-ready AI systems. The role emphasizes applying ML, computer vision, and scientific computing to real-world engineering problems, with collaboration across research and engineering teams.

The ideal candidate will design and optimize models, manage end-to-end ML workflows, and contribute to cutting-edge AI research while translating concepts into scalable