Top Machine Learning Jobs in Houston, TX

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

Convert data science prototypes to production-grade ML tools, deploy and monitor models, run and interpret tests, manage ML platforms, identify data drift, evaluate vendor AI solutions, and communicate technical findings to varied audiences.

The role involves developing AI solutions, conducting research, mentoring juniors, and collaborating with teams to implement machine learning algorithms for complex problems.

Build AI/ML-powered features across ClickHouse Cloud, designing scalable APIs, integrating inference systems and vector DBs, implementing frontend interfaces, and ensuring production-grade monitoring, versioning, and observability for model deployments.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

As a Machine Learning Engineer, you'll architect data pipelines, build ML training workflows, integrate event streams, and collaborate with teams to improve model performance and ensure compliance.

This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

Lead the design and delivery of ML infrastructure and models, mentor engineers, and drive innovation in AI-powered intelligence at Upwork.

Lead design, build, and operation of Twilio's ML and real-time data platform. Architect cloud-native pipelines, feature stores, streaming/batch systems, and low-latency model serving on AWS. Implement MLOps (CI/CD, testing, monitoring), run system design and threat modeling, mentor engineers, and partner with Product, Security, and Compliance to meet privacy and governance requirements.

The Senior Machine Learning Engineer will enhance fraud detection capabilities through ML technologies, improve model performance, and lead high-impact ML projects from experimentation to production.

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.

Lead design, training, and iteration of diffusion-based generative models producing 3D geological models conditioned on geophysical and borehole data; curate synthetic and real datasets; adapt models for projects and collaborate with teams.