Top Remote Machine Learning Jobs in Tallahassee, FL

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

As a Data Science Intern, you will work on computer vision and machine learning projects, focusing on document intelligence and anomaly detection. Responsibilities include designing deep learning models and collaborating with senior team members to prototype solutions.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

Manage product strategies and development for AI/ML SaaS products, oversee full product lifecycle, collaborate with engineering, and implement complex pricing strategies.

The Senior Product Marketing Manager will develop positioning and messaging for Cresta's Travel & Hospitality sector, leadership in market conversation, and go-to-market strategies to drive revenue growth.

The role involves sourcing and recruiting senior engineers in AI, ML, and related fields, building talent pipelines, and collaborating with engineering leadership.

As a Machine Learning Engineer, you'll design and implement detection systems, enhance model efficacy, and analyze datasets to improve email detection against security threats.

The Machine Learning Research Engineer will advance LLM architectures, develop reasoning models, and collaborate on AI/ML solutions for business using Edge AI applications.

Join a technology company to solve complex challenges in digital advertising measurement using data analysis, causal inference, and machine learning. Collaborate with clients and create insights from retail transaction data.

Lead marketing data science efforts, overseeing analytics and machine learning strategies to enhance user acquisition, engagement, and retention. Mentor a team and communicate data insights to executives to influence marketing and budget decisions.

Lead the development and execution of ML-driven User Acquisition products, improving advertiser experience and managing product roadmaps in a fast-paced environment.

As a Senior ML Engineer for Payments, you will develop AI solutions for payment experiences, optimize transaction processing, and ensure system reliability while mentoring teammates and collaborating with cross-functional teams.

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

The DS&ML Group Product Manager oversees Data Science and Machine Learning capabilities, defining strategic vision, managing product portfolios, and ensuring delivery aligned with business needs. Responsibilities include developing roadmaps, executing models, scaling functionalities, and mentoring a team.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Partner Enablement Technical Lead will design and manage technical learning programs for partners, focusing on Data & AI technologies, and align strategies with business needs to enhance partner proficiency.

Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.

Lead the development and integration of advanced AI solutions, focusing on scalable AI models and collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you will design and deploy ML models to optimize clinical trial workflows, mentor junior engineers, and collaborate with cross-functional teams to enhance patient engagement.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.