Top Machine Learning Jobs in Houston, TX

Lead cybersecurity architect responsible for designing and delivering cloud-native security solutions, threat modeling, secure design reviews, automation and CI/CD integration, vendor evaluations, AI-assisted security validation, driving reuse and controls compliance (e.g., NIST 800-53), and advising stakeholders while fostering communities of practice and inclusion.

Lead full-stack engineering on cloud-native (AWS) systems for market and model risk. Design, develop, review, and operate secure production code, drive automation and CI/CD, adopt and validate AI-assisted engineering practices, improve resilience, and collaborate with product and regulatory stakeholders while mentoring teams and evaluating vendor solutions.

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 end-to-end delivery of AI and ML services within Managed Services. Manage project planning, budgeting, execution, and quality. Mentor and develop team members, cultivate client relationships, implement model monitoring and operationalization practices, and collaborate with architects and engineers to ensure compliant, reusable AI solutions.

Lead and grow multiple product-focused software engineering teams building cloud-native, ultra-low-latency, highly resilient payment systems. Drive architecture, microservices decomposition, AWS deployments, engineering practices, cross-team collaboration, mentorship, and adoption of cutting-edge AI tooling to accelerate development and improve system availability and scalability.

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.

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.

Own end-to-end analytical lifecycle to develop and optimize business, risk, and growth strategies. Monitor portfolio and macro trends, build and interpret ML-driven models, lead cross-functional launches, mentor junior analysts, and build AI-assisted workflows to improve decisioning and measurement across products and geographies.

Lead and deliver advanced analytics and machine learning solutions to support pricing, revenue optimization, and partner relationships. Collaborate with cross-functional teams to design, validate, and implement models at scale using large transaction datasets and modern big-data tooling. Translate technical insights into actionable business recommendations.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

Lead applied research on agentic AI for cybersecurity: set scientific direction, run experiments on efficient post-trained models, design evaluation/verification methodologies, partner with product and security teams, and translate research into secure, production-ready agentic systems.

Lead AI strategy, partner engagements, and operational execution across CrowdStrike products. Align R&D and product delivery to company AI strategy, prioritize initiatives, set organizational goals, drive thought leadership, and create order in complex cybersecurity AI environments while delivering customer value.

Intern will own and deliver a scoped engineering project on Deepgram's voice platform (ASR/TTS/LLM/API/SDK), ship reviewed code to staging/production, use AI in development workflows, improve a component measurably, and present results with documentation.

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 and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

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.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Analyze malware and customer detection reports to improve machine-learning based detections, reduce false positives, reverse engineer binaries, review product detections, and support internal teams on threat detection efficacy and remediation.

Manage customer relationships for the Falcon Intelligence Recon product: triage and escalate findings, guide customers on Recon insights, advocate feedback to engineering, and lead process improvements to increase customer satisfaction and renewals.

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.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Lead scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

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.

Lead strategy and execution for enterprise and mid-market GTM across multi-unit restaurant brands. Drive C-suite engagements, modernize sales motions, scale AI-powered forecasting, partner with Product/Engineering, and represent Toast in industry forums to win large, complex contracts.