As a Machine Learning Engineer, you will collaborate with Research Scientists, Data Scientists, and other engineering departments to increase ML productivity through better software and infrastructure. You will improve how we research, train, deploy, serve and monitor our models which will reduce the time it takes to go from idea to production, and enable us to test out new ideas. You will design and implement code and algorithms to help improve our model’s predictive power

Shape the future of AI with Python! As an AI Tutor - Python, you’ll play a vital role in training and evaluating AI models to ensure they generate accurate, relevant, and high-quality information. You’ll use your Python expertise to assess code, solve real-world programming challenges, and help AI systems become better problem-solvers.

As an AI Tutor - C, you’ll play a vital role in training and evaluating AI models to ensure they generate accurate, relevant, and high-quality information. You’ll use your C expertise to assess code, solve real-world programming challenges, and help AI systems become better problem-solvers. This is a unique opportunity to grow professionally in the AI space while deepening your mastery of C.

Join the team to help transform the private markets, and work alongside a talented and collaborative team on a key product feature, bringing cutting-edge AI innovation with executive visibility and high impact. As an intern, you’ll have a hands-on role in designing, building, and testing new AI-driven product features contributing meaningfully to a product that’s reshaping how the private markets operate.

Seismic is looking for Machine Learning Engineer and Data Scientist co-op intern to join our Engineering team! Hard-working individuals with an academic focus on Machine learning, Data Science and software engineering will be building solutions that will drive direct business impact and shape our long-term technical vision with a high-quality bar.

As a research intern within the ML Perception team, you'll apply expertise to real-world multi agent autonomous driving and infrastructure challenges. You will focus on multimodal efficient deep learning for safety critical systems with built in redundancy and robustness, collaborating with a multidisciplinary team to develop innovative models and algorithms to enhance our perception stack.

You’ll be the first MLE on the team, and responsible for building out our ranking system from the ground up. You’ll be in charge of picking the tools, harnessing a diverse set of internal and external data sources, working with Data Science on feature generation, and integrating models directly in our ad serving infrastructure.

You will help build connections across millions of users and business listings using cutting-edge industry tools, including neural networks (NNs), large language models (LLMs), and various embedding techniques for text, images, and videos. You will also apply traditional ML methods such as XGBoost and linear models to enhance our systems. You’ll be responsible for turning raw data into valuable signals and building ML systems end-to-end.

Define and lead the ML roadmap for Canva’s User Voice supergroup, building production-ready NLP models, with a focus on Agentic AI and LLMs, to power user-facing support tools. Build end-to-end ML pipelines for large-scale model training, evaluation, and deployment. You’ll lead Canva’s ML support evolution and help shape how AI transforms how users engage with help at scale.

We are seeking a highly motivated, talented Software Development Engineer for the development and maintenance of Design Automation Infrastructure at SanDisk. Some of the job roles are summarize below: Engage in the development of our simulation automation infrastructure for the design process, enhancing efficiency and accuracy. Utilize machine learning and data analytics techniques to optimize the design process, develop a design recommendation system, identify anomalies, and support failure analysis. Develop and maintain software tools to streamline simulation workflows, mitigate human error, and enhance the analysis of simulation results.