Radical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability.

The opportunity

As an ML Engineer at Radical AI, you will be responsible for developing machine learning systems, data pipelines, and large-scale training infrastructure. You will orchestrate entire machine learning lifecycles, but also data ingestion, enrichment, model exporting and serving, and much more. Your work will directly impact the development of an end-to-end AI-driven approach to materials discovery and development.

Positions are available at various levels of seniority: Senior, Staff, and Principal.

Develop, train, and deploy machine learning models to solve complex problems in materials science and lab automation.

Experiment with cutting-edge ML algorithms and techniques to improve performance and scalability.

Collaborate with researchers on the pre- and post-training stages of model development.

Conduct production-level deployments of our machine learning models and infrastructure.

Continually evaluate model performance and maintain production integrity.

Ensure reproducibility and traceability of models by leveraging version control systems and orchestration tools.

Contribute to research initiatives and participate in knowledge-sharing across teams.

Document workflows, experiments, and deployment procedures for future reference.

Tackle challenging problems with new and different ideas, creativity and contrarian thinking.

Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.

Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, Engineering or a closely related field, or equivalent practical experience.

Proven record of accomplishment in building machine learning systems, working with large generative and/or language models

An excellent understanding of machine learning infrastructure and systems fundamentals.

Strong background in algorithms, data structures, and software engineering principles.

Working knowledge of various generative AI architectures, including transformers, diffusion models, CNFs, and flow matching.

Proficiency in Python and relevant ML libraries (e.g., PyTorch), as well as tools for deploying ML models (e.g., MLflow, K8s, Docker).

Passion for staying current with the latest trends in AI/ML technologies.

Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.

Familiarity with distributed computing frameworks such as Ray, Spark, etc.

Strong fundamental knowledge and practical experience using Linux systems, including working with large-scale computing clusters.

Hands-on experience with MLOps tools (e.g., Kubeflow, Seldon, CI/CD pipelines for ML).

Familiarity with serverless architecture and cost optimization for ML workflows.

Strong publication record in top-tier AI/ML conferences or journals.

A competitive compensation package also includes the best in benefits:

Medical, dental, and vision insurance for you and your family

Mental health and wellness support

Unlimited PTO and 14+ company holidays per year

401K

Work closely with a team on the cutting edge of AI research.

A mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery.

ML Engineer

Quick Summary

Listing Details

Posting Health

4 other jobs at Radicalai

Similar ML Engineer jobs

Stay ahead of the market