Top Machine Learning Jobs in Oklahoma City, OK

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Research Scientist at Upstart will develop machine learning models to enhance borrower risk predictions, design prototypes, and collaborate with cross-functional teams while mentoring junior members.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Margin Analyst collects and analyzes pricing and costing data, monitors margins, manages training for sales teams, and develops strategies to mitigate pricing risks.

As an AI Enterprise Architect, you will translate business needs into AI solution architectures, define reference architectures, and guide AI initiatives from discovery to deployment, ensuring compliance and risk management across solutions.

As a Machine Learning Engineer, you will develop and deploy adaptive ML systems, collaborate with partners, and lead product strategy.

The VP Analyst will provide insights to C-level clients on enterprise application services and AI capabilities, conduct research and analysis, and develop thought leadership content while advising clients on strategies and implementations.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

The Digital Inside Sales Specialist will identify and close digital transformation opportunities in AI, ML, and automation, focusing on B2B sales within targeted accounts while collaborating with internal teams for technical consultation.

Lead the Intelligent Document Processing product to improve extraction and classification accuracy. Define the IDP roadmap, partner with Data Science and Engineering to raise F1/precision/recall, manage ML model lifecycles at scale, benchmark competitors, optimize human-in-the-loop workflows, and ensure extracted data integrity across enterprise systems.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

The Talent Researcher role involves building talent maps in AI, ML, and voice technology, translating hiring signals into research plans, and delivering market intelligence to enhance recruitment processes.

The Senior Product Manager will streamline analytics workflows, manage governance, conduct user research, develop product requirements, and promote AI tools to internal users in healthcare analytics.