Top Machine Learning Jobs in Tampa Bay, FL

The Sr. Product Designer will create user-centered mobile experiences for AI-supported mental health therapy. Responsibilities include designing workflows, collaborating with teams, and utilizing strong design skills in mobile applications.

Define and drive vision for AI-powered tax products, collaborating with experts and engineers to translate needs into scalable solutions.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

The Senior Staff Software Engineer will drive infrastructure improvements and build systems to enhance user experience and growth at Coinbase.

The Senior Machine Learning Platform Engineer will enhance ML capabilities by optimizing streaming pipelines, mentoring junior engineers, and building tools for model performance analysis.

The Principal Product Manager will oversee AI/ML initiatives, drive product development, translate strategy into technical specs, and manage product lifecycle.

Analyze complex challenges and enhance AI infrastructure through advanced machine learning, while mentoring engineers and developing production-grade systems.

As a Machine Learning Platform Engineer, you'll design a centralized platform for ML solutions, advocate for its adoption, manage priorities, write scalable code, debug systems, and integrate with third-party vendors.

As a Senior Machine Learning Engineer, you will design and implement advanced machine learning models and solutions, collaborate with stakeholders, mentor junior engineers, and enhance product capabilities using AI technologies.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

Responsible for building globally distributed ML ecosystems, developing data pipelines, implementing microservices, and collaborating across teams to enhance machine learning technologies.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

As a Machine Learning Intern, you will work on advanced AI solutions, collaborate with teams to design ML systems, and analyze data to enhance user experiences at Dropbox.

As a Machine Learning Platform Engineer, you will enhance ML infrastructure, optimize data pipelines, and support ML model performance, addressing user needs and maintaining high-quality code.

As a Senior Staff Software Engineer, you will design scalable infrastructure for ML models, optimize performance, and collaborate with teams to enhance ML experimentation tools.

Lead AI/ML product strategy and execution. Manage PM team, define product vision and success metrics, ensure compliance, and represent Workiva externally.

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

Lead and manage a team of machine learning engineers to develop AI-driven tools for clinicians, ensuring project success and team growth.

The Principal Product Manager will define and execute the product roadmap for the Data and AI Platform, collaborating with engineering and sales to develop AI-powered identity security solutions.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.