Top Machine Learning Jobs in Houston, TX

Develop high-performance research platforms and tools that bring trading strategies to life. Work in small teams to design, build, and deploy resilient systems using distributed computing, NLP, and machine learning to solve large-data problems in finance.

11-week software engineering internship building high-performance, large-data research platforms and trading tools. Work in small teams on system architectures, distributed systems, NLP and ML, and web frameworks while collaborating with senior engineers.

Lead deployment, configuration, optimization, and operational support of CrowdStrike Falcon AI/ML detection and response capabilities. Tune ML models, build automation playbooks, develop scripts using Falcon APIs, integrate AI features with customer toolchains, support incident response and threat hunting, deliver customer workshops, and mentor team members. Travel up to 25%.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

As an AI Engineering Manager at PwC, you will lead the design and operation of AI-powered platforms, mentor engineers, and ensure project delivery excellence while focusing on security and scalability.

Partner with enterprise customers to design, prototype, and implement CI/CD and DevSecOps solutions. Run discovery and architecture workshops, produce technical proposals and POCs, leverage AI/ML for integrations, and influence product roadmap while building executive-level relationships to drive platform adoption.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead the Creative Serving engineering team to define strategy, roadmap, and execution. Translate business goals into technical deliverables, collaborate with ML and product stakeholders, ensure high-uptime integrations with partner exchanges, provide technical guidance and feedback, enforce engineering best practices, balance short- and long-term priorities, and mentor engineers into future leaders.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

The Director of Product Management for ML Platform will own the product strategy and execution, mentor PMs, and collaborate with ML teams to enhance infrastructure and manage costs.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead transaction monitoring and risk-compliance analytics for the PULSE payments network. Build automated risk programs, partner with data engineering on risk data architecture, conduct root-cause analyses on transactions, and translate technical findings into actionable, regulatory-compliant recommendations for stakeholders and executives.

Own and execute multi-year strategic partnerships with a hyperscaler and an AI lab, aligning technical integrations, commercial motions, and joint go-to-market plans. Coordinate cross-functional teams, run operational cadences, track measurable outcomes (pipeline, ARR, integrations), and represent partnerships to executives while driving hands-on execution and follow-through.

As a Quantitative Research Engineer, design, develop, and implement software for automated trading systems using advanced statistical techniques. Collaborate with researchers and prioritize business needs.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and troubleshoot AI-driven detection models, automation playbooks, API integrations, and threat-hunting for customers. Provide training, mentorship, and customer-facing collateral while optimizing detection efficacy and integrating Falcon into customers' security workflows.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

The role involves leading AI strategy and implementation, overseeing teams, managing client accounts, and delivering strategic business solutions to enhance client value.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Embed in Research to drive end-to-end delivery of STT/TTS model versions and features. Map dependencies and risks, run cross-functional programs, establish lightweight processes, and communicate status across Research, Product, DataOps, and Engineering to ensure timely launches.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.