Machine Learning Engineer - PhD or PhD Candidate (Near Completion)

Machine Learning Engineer - PhD or PhD Candidate (Near Completion) Optimal Inc. - 3.0 Warren, MI Job Details Contract 20 hours ago Qualifications Statistics Git C++ Docker Doctor of Philosophy Model deployment Model training Linux Data collection AI Research & development Machine learning frameworks Prototypes Full Job Description Candidates with only a Master's degree will not be considered.

Minimum qualification:

PhD (completed or currently pursuing with expected completion in the near term) in a relevant technical field. This is an urgent requirement with an anticipated start date within 2 weeks. Priority will be given to candidates who can interview promptly and begin within two weeks of selection. We are seeking a highly motivated Machine Learning / Deep Learning Research Engineer with strong expertise in Machine Learning, Deep Learning, Computer Vision, and AI research. This role is intended exclusively for PhD graduates or candidates near completion from reputable universities. Candidates with a strong academic research background in Machine Learning, Artificial Intelligence, Computer Vision, Data Science, or related fields are encouraged to apply. Research experience gained during a PhD program will be considered equivalent to professional industry experience. This is an urgent hiring requirement, and we are actively seeking candidates who can start within the next 2 weeks. Education Requirement PhD in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field Candidates currently pursuing a PhD with anticipated graduation within the next 3-6 months are also encouraged to apply Only PhD candidates will be considered for this role Candidates with only a Master's degree will not be considered Key Responsibilities Design, develop, train, and optimize Machine Learning and Deep Learning models for real-world applications Own the complete ML lifecycle including data collection, annotation, preprocessing, model training, fine-tuning, evaluation, optimization, and deployment Develop and deploy advanced deep learning architectures including CNNs, LSTMs, ConvLSTMs, Graph Neural Networks (GNNs), Reinforcement Learning, and Transformer-based models Conduct experiments, evaluate model performance, and drive continuous algorithmic improvements Work with large-scale datasets for model training, validation, and testing Optimize and deploy AI models for scalable and efficient real-world applications Translate research concepts into scalable, production-ready AI systems Collaborate with cross-functional engineering and research teams to integrate ML models into real-world applications Document methodologies, experimental findings, and technical solutions Contribute to technical innovation initiatives and advanced AI research activities Required Qualifications Strong PhD research background in Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision, Data Science, or related areas Strong programming experience with Python and C++ Hands-on experience with PyTorch, TensorFlow, Keras, Scikit-learn, or similar ML frameworks Strong understanding of Machine Learning, Deep Learning, Neural Networks, and AI algorithms Experience developing and training advanced deep learning models and architectures Solid mathematical foundation in linear algebra, probability, statistics, optimization, and applied machine learning Experience working with Linux environments, Git, Docker, and modern development workflows Demonstrated research experience through publications, thesis work, academic research projects, or equivalent research contributions Strong ability to independently research, prototype, and deploy AI solutions Preferred Qualifications Publications in leading AI, Machine Learning, or Computer Science conferences/journals Experience transitioning AI/ML models from research environments into production systems Experience with

CUDA, GPU

acceleration, distributed computing, or high-performance computing Experience handling large-scale, real-world datasets This role is ideal for candidates passionate about applying advanced AI research, machine learning, and deep learning techniques to solve challenging real-world problems.