Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., LLM, deep learning, convolutional networks). As a Customer Engineer, you will work with technical Sales teams as a machine learning subject matter expert to differentiate Google Cloud to our customers.

To achieve our ambitious goals, we’re looking for a Machine Learning Engineer to join our Core Product team. As a Machine Learning Engineer in Core Product, you will have a significant customer-facing impact, which includes defining the personalized customer experience.

Work on cutting edge Trust & Safety Machine Learning solutions for detecting fraud, mitigating fake accounts and account takeovers, detecting image and text policy violations, reducing data scraping, and others.

Familiarity with machine learning frameworks such as PyTorch or Tensorflow. This role is crucial; you will be at the forefront of integrating machine learning into our core products, from error classification to predictive analytics for application performance monitoring.

Experience with cloud platforms (e.g., AWS, Azure, GCP, OCI) and their machine learning services. Experience with building and optimizing machine learning pipelines using tools like Apache Airflow, Kubeflow, or MLflow.

Join us in revolutionizing how businesses harness the power of machine learning to unlock the potential of unstructured data. Build infrastructure to enable training and serving large scale machine learning models on image and video datasets.

Experience with machine learning lifecycle management and LLM deployment strategies. As a Machine Learning Engineer at Radiant Security, you'll be instrumental in designing, developing, and deploying sophisticated AI systems.

Our machine learning systems monitor and surface suspicious activity (money laundering, illegal activity and terms of service violations) for agent review. We use Machine Learning and Generative AI as an important part of our toolkit.

As a Trust and Safety Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. Have experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch.

Insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. Demonstrated in-depth knowledge in the foundations and practice of modern machine learning, including deep learning, and their application to diverse molecular design tasks.

Mosaic AI is hiring experienced machine learning platform engineers to build out our generative AI platform for the ML model development lifecycle including pre-training of large language models (LLMs), fine-tuning, evaluation, and serving.

Our founders bring machine learning and product experience from the world's leading technology companies (Facebook, Instagram, Primer.ai and Cloudera) and institutions (Stanford, Cambridge and UIUC.

The Machine Learning Infrastructure Engineer will be responsible for architecting, building the compute infra that powers training and serving of our models. Design, build, and maintain scalable machine learning infrastructure to support our model training, inference and applications.

Strong understanding of machine learning approaches and algorithms: Deep Learning, LLM, Generative Models, NLP. PhD in a relevant field (computer science, machine learning, AI, statistics, physics.

We are looking for ambitious and agile data scientists that would like to seize the opportunity to work on some of the most challenging productive machine learning and big data platforms worldwide, processing some 600B events every day and making some 5B predictions.