Top Senior Machine Learning Jobs in Houston, TX

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

The role involves developing and maintaining machine learning models and infrastructure, defining technical vision, and leading cross-functional initiatives for scalable ML systems.

As a Staff AI Engineer, you will drive product-centric development of AI technologies, enhance evaluation systems, optimize reasoning strategies, and lead production-grade model tuning while balancing performance and cost.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

Lead the design and scaling of ML infrastructure, work on model lifecycle, optimize workflows, and mentor engineers in a fast-paced AI environment.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves designing and maintaining backend systems for ML applications, working closely with cross-functional teams, and optimizing AWS services.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

As VP of Engineering, you'll lead the application engineering strategy and team, integrating AI capabilities into products while ensuring quality and execution across backend, mobile, and desktop platforms.

Own and execute the billing, financial, and corporate systems product roadmap. Define end-to-end experiences, lead 1-2 scrum teams, prioritize work using qualitative and quantitative data, and collaborate across Finance, Receivables, HR, analytics, UX and commercial teams to deliver automated, data-driven solutions that improve billing and financial functions.

The Data Scientist II will design and deploy ML models for autonomous vehicles, enhance data tagging, and improve dataset quality through advanced techniques and frameworks.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

Lead the creation and implementation of AI architectures, translating business needs into AI solutions while mentoring teams and ensuring compliance with security standards.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The role involves automating and maintaining AWS infrastructure, collaborating with engineering teams for deployment, optimizing ML infrastructure, and ensuring compliance and security standards in a cloud-native environment.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

As an AI Specialist SC, you will support major global clients by offering presales machine learning solutions, driving business transformations and technical discussions, while collaborating across teams.

The Specialist Solutions Architect will design production-grade ML & AI applications, optimize AI workloads, and provide technical support while collaborating across teams to enhance Databricks' offerings.

The Lead ML Ops Data Scientist will design scalable MLOps systems, mentor data scientists, and develop models for rental matching and personalization.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.