Top Machine Learning Engineer Jobs in Los Angeles, CA

The Staff Machine Learning Engineer will lead projects, develop ML solutions, mentor the team, and ensure engineering best practices in conversational AI at Square.

Lead modeling efforts on projects, mentor junior engineers, and implement AI advancements to enhance Square products. Collaborate on ML opportunities.

The Signal Processing AI and Machine Learning Engineer will support research and technical programs, applying standard techniques in a team environment. Candidates should possess strong coding skills, preferably in C++ or Python, and will receive training and mentorship. A Master's degree in a related field is required, along with the ability to obtain a security clearance.

The Staff Machine Learning Engineer will work on the Cash App's Risk team, developing analytical and ML solutions to mitigate risks and fraud across Cash App products, collaborating with cross-functional teams to balance regulatory risks and customer experience.

The Staff Machine Learning Engineer will lead machine learning projects focused on conversational and generative AI at Square. Responsibilities include developing ML products, collaborating with business leaders, driving cross-functional projects, mentoring team members, and advocating for best practices in engineering.

The Staff Machine Learning Engineer will collaborate with product and marketing teams to develop and implement personalized machine learning models aimed at enhancing customer engagement and accelerating growth for Cash App. Responsibilities include building, deploying, and optimizing ML models while contributing to the strategy around personalization initiatives.

Lead modeling efforts for core Square products, discover ML opportunities, mentor junior engineers, and make strategic decisions for model deployment and maintenance, leveraging expertise in computer vision and NLP to enhance product functionality.

The Lead Machine Learning Engineer will drive innovation by applying machine learning models to enhance streaming services, improve developer efficiency, and develop scalable data analysis methods. This role involves mentoring team members and collaborating with product teams to define strategies and optimize algorithms through continuous production rollout.