Top Machine Learning Jobs in Houston, TX

The Engagement Manager manages project execution, collaborates with technical teams on AI solutions, develops client relationships, and coaches consultants.

The Engagement Manager leads client projects, manages teams, ensures timely delivery, develops client relationships, identifies business opportunities, and provides thought leadership.

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work on-site with portfolio companies to design, prototype, and deliver full-stack digital and AI solutions. Lead discovery, deployment, and post-launch iteration, ensure security/compliance, resolve technical issues, mentor teams, and drive enterprise integrations and adoption. Frequent domestic travel and stakeholder management required.

Sell Litify's AI-driven legal operating platform to law firms and legal departments. Manage full upsell motions, consult on AI adoption, deliver high-level demos to C-suite, meet sales targets, and articulate ROI of autonomous agents and AI integrations.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

Develop autonomy software for mining vehicles, including perception, SLAM, motion planning, control, sensor fusion, localization, and mapping. Integrate LiDAR, cameras, radar, IMU, and GNSS while building embedded real-time systems. Create simulation, logging, and data pipelines, and validate autonomy software through bench, rig, and field testing. Collaborate with hardware, controls, and systems engineers to deliver safe, reliable vehicle autonomy.

The role involves developing and managing MLOps pipelines, deploying machine learning models, collaborating with various teams, and ensuring system reliability in oil and gas operations.

Design and deploy agentic AI systems, build ML pipelines, optimize production models, and lead enterprise data standardization and governance initiatives. The role collaborates across business and technical teams to identify AI use cases, establish data quality and metadata standards, promote data literacy, advise on AI best practices, and ensure scalable, reliable, compliant AI solutions.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Lead government relations in the Western U.S. to drive adoption of AI-powered school bus safety solutions. Build relationships with municipal and state officials, school leaders, and law enforcement; advocate for legislative and regulatory changes; run grassroots campaigns; monitor policy developments; represent the company at hearings and events; and collaborate with Sales, Marketing, and Legal.

Build and maintain ML and generative AI tooling, training and inference platform services, model evaluation and testing frameworks, and APIs to expose ML products. Deploy and manage applications across the AI/ML SDLC, mentor teammates, and write production-quality code daily.

Build and deploy production machine-learning systems within client environments, covering data discovery, modeling, validation, deployment, scheduling, monitoring, and retraining. Develop forecasting and detection models for imperfect time-series data, establish honest evaluation and KPI frameworks, and ship usable APIs or interfaces. Work directly with client IT and data teams through discovery, demos, and feedback cycles. The role also involves data engineering, software development, basic cloud and DevOps work, and advising clients when ML is not appropriate.

Design, build, and deploy novel sensor hardware and data acquisition systems; curate geoscientific datasets; develop statistical, physics-based, and ML models (2D/3D) to predict mineralization; create visualizations and evaluation tools; collaborate with geoscientists, engineers, and vendors; deploy sensors in the field and integrate results to guide exploration programs.

Lead perception vision, strategy, and roadmap for AV perception. Drive advances in detection, classification, tracking, fusion, and prediction; design sensor suites; define KPIs; hire and manage engineering teams; coordinate cross-functional deployment and issue resolution to ensure robust commercial autonomy performance.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.