Top Remote Machine Learning Jobs in Tulsa, OK

As a Staff Machine Learning Engineer on the Bidding Policy team at Liftoff, you will work on building state-of-the-art ML models to make accurate bidding decisions in millions of auctions per second. You will have end-to-end ownership of designing and implementing reliable, scalable, and cost-efficient systems.

Design, build, evaluate, deploy, and iterate on large scale Machine Learning systems at Dropbox. Collaborate with cross-functional teams to personalize user experiences and impact millions of users. Requires BS or MS in Computer Science, 2+ years of experience, strong analytical and problem-solving skills, and proficiency in Python, C, and C++.

Join Enigma as a Senior Machine Learning Engineer to lead the development of entity resolution algorithms, predict small business behavior, and enhance machine learning infrastructure. Build scalable ML systems and collaborate with cross-functional partners to drive impact on the small business economy.

Work as a machine learning engineer in the Applied AI and Machine Learning team. Contribute to core recommender systems and machine learning models. Opportunity to work on a large-scale machine-learning system and continuously learn and improve the solution.

Join Spring Health as a Machine Learning Engineer to build and enhance models for precision mental health solutions. Contribute to AI platform development and improve member and provider experiences through innovative data products.

Seeking a Senior Machine Learning Engineer passionate about building impactful and engaging ML products. Responsible for building and deploying ML models, introducing new infrastructure, and collaborating with peers to bring new features into production. Must have 5+ years of experience in ML engineering or data science.

Responsible for leading the use of data to make decisions, development of machine learning algorithms on geospatial data, assisting in the recruitment and mentorship of junior data scientists, managing medium to high complexity projects, and collaborating with cross-functional teams to create innovative products.