AI Research Scientist / Machine Learning Engineer (PhD) [33320]

We are seeking a PhD-level AI Research Scientist or Machine Learning Engineer to develop cutting-edge AI and machine learning solutions that power next-generation products. You will work at the intersection of research and engineering, transforming advanced ML techniques into scalable, production-ready systems.This role is open to:PhD graduates with 4+ years of industry experience in AI, machine learning, or applied research.Machine Learning Engineers with a PhD and 1–2 years of professional ML engineering experience, provided they have demonstrated success deploying production ML systems.ResponsibilitiesResearch, design, and develop advanced machine learning and AI models.Build and deploy production-ready ML systems and inference pipelines.Collaborate with software engineers to integrate AI capabilities into customer-facing products.Optimize model accuracy, efficiency, and scalability.Develop data pipelines, model evaluation frameworks, and experimentation workflows.Stay current with the latest advancements in machine learning, deep learning, LLMs, and generative AI.Mentor engineers and contribute to technical strategy and architecture.Publish or present research where appropriate and translate research into business impact.QualificationsPhD in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Statistics, Applied Mathematics, or a related quantitative field.4+ years of industry experience in AI/ML research or engineering OR1–2 years of experience as a Machine Learning Engineer with proven experience deploying ML models into production.Strong programming skills in Python and experience with C++, Java, or Go.Hands-on experience with PyTorch, TensorFlow, or JAX.Experience building scalable ML pipelines and distributed training or inference systems.Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies.Strong understanding of algorithms, deep learning, and software engineering best practices.Preferred QualificationsExperience with Large Language Models (LLMs), generative AI, multimodal models, or reinforcement learning.Experience with distributed systems, MLOps, Kubernetes, Docker, and CI/CD.Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL) are a plus.Startup or high-growth technology company experience.Strong communication skills with the ability to collaborate across research and engineering teams.