Top Machine Learning Jobs in Houston, TX

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

The VP of Sales will drive enterprise adoption of AI-powered healthcare software, engage with stakeholders, and shape go-to-market strategies for new AI products.

The Expansion & Vertical Marketing Manager drives global marketing strategies, focusing on product-led expansion, vertical execution, and scalable programs rooted in customer outcomes and aligned with business objectives.

As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.

Lead the vision and strategy for the Commerce Intelligence Platform, transforming data assets into scalable, revenue-generating products, fostering cross-functional collaboration and driving market growth.

The VP of Client Development will lead InMobi's growth strategy within the OEM and Telco sectors, establishing executive partnerships, joint business plans, and aligning product innovation to maximize market opportunities. The role requires extensive experience in enterprise partnerships and strategic business development with global technology leaders.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

Lead a team to enhance Cengage Learning Platforms by implementing AI-first strategies, improving software delivery processes, and ensuring product quality.

Lead the Performance ML team at MNTN, driving strategy and deployment of predictive models for ad technology, while managing, mentoring, and scaling engineering teams.

Lead vision, strategy, roadmap, and commercialization for the Juno Labs product portfolio. Manage and scale product teams, establish governance and processes, drive AI-enabled product initiatives, partner cross-functionally to translate requirements, and define KPIs to ensure product-market fit and growth.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.

Lead and coach Agile software teams, facilitate Scrum ceremonies, manage timelines, risks, and stakeholder communication, and support delivery of AI-enabled solutions across client engagements in a distributed consulting environment.

Owner of customer success for a portfolio of industrial accounts, leading project delivery from scoping to commissioning and sustainment. Drive value realization, risk mitigation, cross-functional coordination, executive communication, and identify expansion opportunities while liaising between customers and product/R&D.

Lead and build the full demand generation function: inbound, outbound-assist, ABM, field, and digital. Own pipeline metrics (MQLs, SQLs, pipeline contribution), run integrated enterprise campaigns, manage marketing tech stack (CRM, MAP, intent, analytics), and align closely with Sales on ICP, messaging, and pipeline quality.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

Embed with customers to discover needs, design and implement production-grade integrations (APIs, data pipelines, event-driven workflows), deploy and troubleshoot solutions, train IT teams, and drive adoption and measurable business outcomes.

Perform data collection, cleaning, validation, and analysis on large client datasets using Python, SQL, and spreadsheets. Produce actionable insights and business narratives, automate data workflows, and support text/document annotation to generate labeled data for NLP and LLM solutions. Collaborate with senior analysts and improve internal analytical processes and tool configurations.