Top Senior Machine Learning Jobs in Houston, TX

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

Lead end-to-end product strategy and delivery for a core marketplace area, collaborating with engineering, UX, and design. Conduct qualitative and quantitative research, run agile sprints, measure results with analytics, and pioneer AI/ML product features and workflows to improve user experience and platform impact.

Lead go-to-market for Mapboxs AI products: define positioning, messaging, and launch strategy; drive customer research, sales enablement, content, and cross-functional alignment to accelerate adoption of AI-powered location capabilities.

Lead and grow an applied science team building reliable, production-ready generative AI systems for legal use. Own end-to-end AI system readiness, set technical direction, perform evaluations and error analysis, partner cross-functionally to move work to scale, hire and coach staff, and represent the team externally.

Lead development and application of analytics, statistical models, and dashboards to support R&D Quality oversight. Integrate clinical, safety, lab, and operational data to identify risks, support audit/inspection readiness, enable RBQM, and provide actionable quality insights and recommendations to cross-functional partners.

Lead strategic vision and execution of next-generation bioinformatics technologies. Identify and evaluate emerging computational methods, translate research into production-grade pipelines and prototypes, support product roadmaps and technology transfer, and partner cross-functionally to commercialize genomic and AI-driven healthcare solutions.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Provide senior legal and regulatory counsel for digital health and medical device products (SaMD), guiding product lifecycle, FDA and global filings, AI-enabled features, labeling, compliance, post-market obligations, and cross-functional governance. Lead strategy, manage external counsel, and translate regulatory developments into business guidance.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.

Lead product management for AI tools in software/SaaS, manage product lifecycle, drive strategic roadmap, and ensure product adoption through iterative shipping and user feedback.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Lead Buildertrend's end-to-end payments risk and operations: merchant onboarding, underwriting, transaction monitoring, disputes, chargebacks, and portfolio management. Build AI-assisted fraud prevention, scale automation, embed risk controls with Product and Engineering, develop analytics and governance, and grow a high-performing team to balance risk and business growth.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

Design, implement, and validate autonomy software for mining vehicles including perception, localization, mapping, motion planning, and control. Integrate and calibrate LiDAR, camera, radar, IMU/GNSS sensors; build embedded real-time software; develop simulation and data pipelines; and lead bench, rig, and field validation while collaborating with hardware and controls teams.

Lead discovery and design of end-to-end enterprise AI/ML architectures, define MLOps/LLMOps and data lifecycles, integrate solutions with enterprise systems and security, produce reference patterns and runbooks, mentor teams, and scale repeatable delivery through accelerators while partnering with clients and risk/security stakeholders.

Lead end-to-end ML system development: data exploration, model research, training, deployment, evaluation, and MLOps. Collaborate cross-functionally to prioritize claims, improve matching, measure business impact, and own a technical workstream.

Design and scale production AI/ML systems, including autonomous agents, LLM integrations, retrieval pipelines, and virtual assistants with voice capabilities. Build and optimize models, training and deployment pipelines, APIs, and cloud-native services. Apply agent frameworks, vector databases, RAG, fine-tuning, observability, and MLOps practices. Collaborate on architecture, evaluate emerging reasoning and tool-use approaches, and mentor engineering peers.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Sell HiddenLayer's AI security platform to federal agencies by developing account strategies, driving pipeline and revenue, leading technical and executive engagements, navigating federal acquisition and contracting, coordinating cross-functional teams, and supporting adoption, expansion, and renewals across the Intelligence Community, DoD, DHS, and civilian agencies.