Top Senior Machine Learning Jobs in Houston, TX

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Supports pre-sales execution for AI security solutions through technical discovery, architecture reviews, demonstrations, proof of concepts, deployment assistance, partner enablement, and customer training. The role develops sales engineers, manages demo environments, supports channel partners, facilitates technical handovers, and engages CTOs, CISOs, and AI leaders. It requires AI security expertise, cloud deployment experience, containerization, Kubernetes, and strong technical communication skills, with travel up to 50%.

Owns go-to-market execution and quota-carrying sales for Fortinet’s AI security solutions. Responsibilities include building pipeline, closing complex enterprise deals, presenting to executives, conducting discovery workshops and demonstrations, training account teams and partners, consulting on AI security architectures, and developing strategic customer relationships. The role requires expertise in AI technologies, cloud platforms, enterprise security, executive engagement, and complex six- and seven-figure sales.

Develop data pipelines, machine learning models, statistical algorithms, and physics-informed models for downhole tools, signal processing, and formation evaluation. Analyze large structured and unstructured datasets, simulation outputs, and experimental data. Build analytics tools, automate workflows, and collaborate with engineers, physicists, and product teams to support tool development. Communicate technical findings, contribute to project planning and documentation, and apply oil and gas domain expertise to improve system understanding.

Leads the architecture, development, deployment, and delivery of production AI, machine learning, generative AI, and public health analytics solutions. Translates client objectives into technical requirements, roadmaps, and architectures; guides multidisciplinary teams; manages technical risks; and serves as the primary client liaison. Establishes secure software engineering, MLOps, DevSecOps, responsible AI, privacy, governance, testing, monitoring, and documentation practices. Develops AI applications, RAG workflows, intelligent agents, APIs, and reusable components in cloud environments.

Leads end-to-end solution architecture for complex enterprise initiatives across business processes, applications, data, integrations, cloud, security, and operations. Advises cross-functional stakeholders, establishes architecture standards and governance, evaluates risks and technology options, shapes roadmaps, and guides implementation. The role focuses on Corporate Functions and Order-to-Cash, with expertise in SAP S/4, SAP MDG, automation, enterprise integration, and regulated operational environments. It also mentors architects and delivery teams while ensuring solutions align with business strategy and measurable outcomes.

Drive adoption, value realization, and expansion of Neara’s enterprise SaaS platform among strategic customers. Build customer ROI and business cases, translate technical capabilities into business outcomes, deliver training and workshops, manage stakeholder relationships, and advise on workflows and change management. Collaborate with Sales and Deployment teams to support customer success, account growth, and measurable value delivery, particularly across infrastructure and energy-sector customers.

Owns BI product strategy for Quote-to-Cash and Order-to-Cash processes. Partners with Finance, Sales, Legal, Product, FinSys teams, and engineering to identify operational friction and translate it into BI, AI, and machine learning opportunities. Creates PRDs, roadmaps, functional requirements, and downstream data products supporting quoting, deal structuring, billing, entitlements, contracts, and revenue recognition.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and data modernization. Partners with executives and cross-functional leaders to establish data ownership, improve quality, develop analytics and KPI frameworks, prioritize AI use cases, and measure transformation value. Builds data-focused organizational capabilities, drives adoption and data literacy, develops investment cases, and guides enterprise initiatives that improve forecasting, planning, operational decisions, and business outcomes.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and modernization initiatives. Establishes data ownership models, roadmaps, KPIs, and governance frameworks while partnering with executives and business functions. Builds data and analytics capabilities, develops investment cases, drives transformation value realization, promotes data literacy, and leads cross-functional change to improve decision-making and business outcomes.

Leads wind energy assessments, SCADA and performance analysis, advanced data processing, automation, and technical consulting for utility-scale renewable projects. Develops analytical tools and workflows, evaluates energy production, uncertainty, losses, and risks, and provides technical oversight, peer review, mentoring, and customer-facing expertise. The role also advances AI-enabled analytics, data management, visualization, and renewable energy assessment methodologies.

Performs wind resource and energy production assessments for utility-scale projects, analyzing meteorological, SCADA, LiDAR, and operational data. Supports technical due diligence, project performance and risk evaluations, remote sensing, uncertainty analysis, and customer deliverables. Collaborates with multidisciplinary teams, mentors colleagues, contributes to AI-enabled automation and analytical workflows, and participates in technical consulting projects across the renewable energy lifecycle.

Design, develop, and integrate Generation Management System (GMS) software; collaborate with customers on configuration, testing, training, and issue resolution; support proposals; ensure regulatory compliance; work with SCADA/EMS integrations and power system modeling/optimization.

Account Director responsible for enterprise sales across energy and chemistry markets. The role involves qualifying complex R&D and product development opportunities, generating pipeline, engaging Fortune 1000 stakeholders, presenting value-based business cases, building consensus, closing enterprise deals, and contributing customer insights to product strategy. Requires 50% travel to customer sites and industry events, collaboration with technical teams, and a consistent record of exceeding sales quotas.

Define and scale autonomous agricultural machinery products through customer research, experimentation, roadmap prioritization, system requirements, and cross-functional delivery. Partner with engineering and commercial teams on hardware, embedded software, computer vision, machine learning, navigation, controls, and mobile solutions. Use data, field feedback, and performance metrics to improve adoption, customer confidence, mission quality, and product impact.

Provides pre-sales technical expertise for MPC and APC solutions. Leads customer discovery, opportunity qualification, benefits studies, process and historical data analysis, solution scoping, proposal development, technical presentations, and sales handoffs. Assesses manufacturing processes, quantifies business value, develops engineering estimates and bills of materials, addresses technical objections, and supports strategic sales pursuits. The role requires manufacturing or customer-support experience, 40% travel, and strong knowledge of process optimization and control strategies.

Own enterprise sales across new and existing accounts, leading consultative, ROI-driven sales cycles from discovery through close. Develop account plans, build executive relationships, collaborate with Solutions and Forward Deployed Engineers, forecast pipeline, maintain CRM discipline, lead business reviews, represent the company at industry events, and relay customer insights to shape the product roadmap.

Develop graduate-level Applied AI course materials, including lessons, labs, case studies, assignments, rubrics, projects, readings, templates, and videos. Design practical activities using LLMs, RAG, AI agents, automation, APIs, and evaluation tools. Collaborate with learning designers and university faculty, explain complex concepts to nontechnical learners, maintain academic quality, and update content as AI tools and regulations evolve.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads Fenergo product consulting engagements focused on AML, sanctions, data analytics, and regulatory risk solutions. Manages client accounts, oversees project planning and execution, guides analytics initiatives, and develops data-driven business strategies. Uses predictive analytics, machine learning, statistical modeling, and scenario analysis to generate insights. Manages and mentors teams, engages stakeholders, resolves conflicts, promotes innovation, and ensures high-quality deliverables and adherence to professional standards.

Leads technology consulting engagements involving technology, data, and AI strategy; software and architecture assessments; analytics and business intelligence; program delivery; business cases; product roadmaps; and due diligence. Manages client stakeholders, workstreams, deliverables, priorities, and junior team members while developing strategic insights, resolving complex issues, supporting sales, and delivering large-scale technology programs.

Drives business transformation and strategic change initiatives by developing transformation strategies, improving processes and organizational design, managing change adoption, engaging senior stakeholders, coordinating cross-functional projects, delivering training, and tracking benefits realization. The role manages transformation projects from planning through post-implementation review while ensuring alignment with business objectives, timely delivery, budget adherence, and successful organizational adoption.

Develop fraud detection and identity-risk machine learning models from problem definition through production deployment. Responsibilities include investigating fraud patterns, exploratory analysis, feature engineering, model training and evaluation, production-quality Python and PySpark development, monitoring model and feature drift, and presenting analytical recommendations. The role requires collaboration with data scientists and engineers while addressing privacy, explainability, validation, governance, and real-world fraud-modeling challenges such as class imbalance and delayed labels.

Leads AML transaction monitoring optimization, including rule testing, threshold tuning, scenario design, and alert reduction. Drives FIU automation and workflow improvements, evaluates AI-enabled compliance tools, and partners with Product, Engineering, Data, Operations, and vendors on monitoring infrastructure and integrations. Supports scalable compliance controls across new products, jurisdictions, and transaction volumes while maintaining regulatory alignment and detection effectiveness.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.