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Top Machine Learning Jobs in Houston, TX
As a Client Partner, you will drive growth by targeting and closing new enterprise clients with a consultative sales approach. You'll develop relationships with senior executives, articulate the value of the Aera Decision Cloud, and collaborate with cross-functional teams to achieve revenue targets.
The Senior Machine Learning Engineer will develop, train, document, and manage machine learning models, collaborating with product teams and the community to enhance Wikipedia and similar projects. Key responsibilities include assessing customer needs, scoping tools, gathering training data, deploying models, and monitoring their performance over time.
As a Senior Machine Learning Engineer, you will develop, train, document, deploy, and manage production machine learning models. You will collaborate with internal and external customers to build scalable models and support other teams in the Foundation while ensuring the effectiveness of machine learning solutions.
As a Senior Machine Learning Engineer at the Wikimedia Foundation, you'll plan, develop, train, document, deploy, and manage production machine learning models. You'll collaborate with internal and external customers to build and maintain scaled models, assess needs, gather training data, and ensure ongoing monitoring and improvement of the models.
The Senior Machine Learning Engineer will develop, train, document, deploy, and manage production machine learning models for the Wikimedia Foundation. The role involves collaboration with internal teams and the broader community to assess needs and implement scalable machine learning solutions, particularly in NLP tasks while working in a remote environment.
The Senior Machine Learning Engineer will plan, develop, train, document, deploy, and manage machine learning models, collaborating with internal and external teams to meet project needs and monitor model performance over time.
The Senior Machine Learning Engineer will develop, deploy, and manage production machine learning models, collaborating with internal and external customers and teams. Responsibilities include training models, monitoring their performance, and providing insights to improve projects like Wikipedia.
Responsible for planning, developing, training, documenting, deploying, and managing production machine learning models, while collaborating with internal and external customers to assess needs and gather training data.
The Principal Engineer - ML/AI will design, develop, and deliver advanced AI and machine learning solutions, translating technical innovations into strategic business outcomes. The role requires leadership in AI, innovative problem-solving, and a comprehensive understanding of emerging technologies to serve the Federal Government clients effectively.
As a Software (ML Product) Engineer at iterative.ai, you will enhance user workflows for DVC, collaborate with technical product managers, and improve MLOps practices within ML teams. Responsibilities include optimizing the tool’s usability and driving projects like dvclive, emphasizing software engineering skills and communication.
As a Senior Software Engineer II for ML Core, you will define architecture and implement changes for backend services. Responsibilities include optimizing search infrastructure, enabling rapid ML model productionalization, mentoring team members, and managing complex projects across teams.
As a Machine Learning Solutions Architect, you will design and implement data solutions tailored to customer needs, manage deployment strategies, and collaborate with data scientists to ensure machine learning models are viable and effective in production. You will also provide thought leadership on technology recommendations and oversee the integration of data systems to enhance model performance and business insights.
The Senior Software Engineer II will define architecture and implement changes across backend services for scalable solutions. Responsibilities include optimizing search infrastructure, advocating system designs, overseeing complex projects, mentoring team members, and adapting to change while focusing on customer experience and project quality.
As a Senior Machine Learning Engineer at Enigma, you will develop scalable ML systems, enhance entity resolution algorithms, and improve machine learning infrastructure, directly impacting business decisions for customers. You will collaborate with data scientists and engineers to innovate and maintain high-performance systems.
As a Senior AI/ML Engineer, you will develop and deploy Machine Learning models, collaborate with a cross-functional team, and work on building and maintaining machine learning pipelines with a focus on innovation and interdisciplinary teamwork.
The Senior Manager of Machine Learning Engineering oversees the productionization and deployment of ML models to optimize manufacturing costs and pricing. This role involves leading a team of engineers, ensuring high standards in model performance and scalability, collaborating with cross-functional teams, and driving continuous improvement in engineering practices.
The Staff, Machine Learning Engineer will develop and deploy machine learning models, collaborate across teams to implement statistical models, leverage advanced technical stacks for scalable AI solutions, integrate enterprise data sources, and harness LLMs to drive innovation in AI at Twilio.
As a Senior AI/ML Engineer at Twin Health, you will develop AI-powered systems, optimize ML models, and collaborate across teams to enhance member health outcomes. Your work will involve utilizing advanced techniques in reinforcement learning and deep learning to provide personalized health recommendations.
The Practice Director will lead the Data Engineering and AI/ML practice, managing customer engagements and focusing on Data Modernization. Responsibilities include strategic planning, team leadership, guidance on data solutions, and operational management while ensuring excellence and innovation in delivery.
The Sr. AI/ML Engineer III will analyze complex datasets, apply machine learning techniques, present results, and lead technical design and support for identity management systems. They will also engage with federal leadership, providing expertise in security architecture and data solutions, specifically in a cloud environment using AWS and graph data science techniques.
The Senior Big Data Engineer will develop scalable batch processing systems using the Hadoop ecosystem and manage Machine Learning pipelines. The role requires strong programming skills in Java and Python, knowledge of GCP for data processing, and extensive experience in engineering complex systems. The candidate should excel in remote collaboration and maintain effective communication with team members.
As a Sr. ML Ops Engineer, you'll develop and maintain scalable ML pipelines, automate workflows, monitor and optimize model performance, collaborate with teams, ensure compliance, and document ML processes and performance.
As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, work collaboratively with engineers, engage with clients, and mentor project teams, focusing on practical AI solutions for clients.
Design and implement machine learning solutions for a Conversational AI platform and new product. Collaborate with cross-functional teams to architect scalable ML systems. Stay updated on the latest ML technologies and incorporate them into solutions.
As a Staff Software Engineer - ML, you will develop and manage relevance models to enhance user experience on Eventbrite. Collaborating with various teams, you will tackle machine learning, search ranking, and recommendations to ensure the right content is presented to users.
Top Companies in Houston, TX Hiring Machine Learning Roles
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