Top Senior Machine Learning Jobs in Houston, TX

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

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%.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

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.

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.

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

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.

Own BI product strategy for Quote-to-Cash and Order-to-Cash financial systems. Partner with Finance, Sales, Legal, Product, and Engineering to identify operational friction, translate needs into BI and AI/ML opportunities, author PRDs and roadmaps, and ensure quoting, contracting, billing, and revenue-recognition processes are accurately represented in downstream data products.

Own applied computer vision and machine learning model development from problem definition through production deployment. Build and fine-tune solutions for object detection, segmentation, classification, video analysis, forecasting, anomaly detection, regression, and clustering. Evaluate model performance and account for real-world constraints involving lighting, sensors, data quality, and edge-device computing limitations.

Own full-cycle global recruiting across technical, go-to-market, and corporate functions. Partner with hiring managers and senior leaders on structured interviews, sourcing, prioritization, and hiring enablement. Manage recruiting metrics and reporting in Greenhouse, improve processes and workflows, strengthen employer brand, and deliver an excellent candidate experience. The role focuses on hiring for niche industrial software, AI/ML, and process engineering positions in a fast-growing company.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

Develop and deploy production machine learning and AI solutions for customer and product needs. Build proofs of concept, MVPs, AI agents, and scalable workflows; integrate tools such as MLFlow, Spark, LangChain, Kubeflow, and Kubernetes; optimize models for performance; translate requirements into product enhancements; collaborate cross-functionally; document best practices; and mentor junior engineers.

Lead the strategy, roadmap, development, commercialization, and adoption of AI-powered products for drilling operations. Partner with Operations, Engineering, HSE, Data Science, Software Engineering, customers, and technology providers to deliver solutions using generative AI, computer vision, machine learning, automation, and modern data platforms. Build and lead a multidisciplinary organization, manage AI initiatives and investments, establish technology standards and governance, and drive organizational change across drilling operations and customer environments.

Lead forecasting, supply and logistics planning to ensure on-time deliveries and cost efficiency. Use digital tools, AI/ML, and real-time job data to optimize supplies, monitor suppliers, adjust forecasts, and support field operations. Train and advise engineers, identify cost-saving opportunities, and develop improved workflows and machine-learning tools for the supply chain control tower.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Drive enterprise sales and client adoption of Aera’s Decision Intelligence platform. Responsibilities include targeting and closing large enterprise clients, expanding existing accounts, managing C- and VP-level relationships, developing account strategies and transformation roadmaps, articulating technology value, collaborating cross-functionally, and exceeding customer revenue and ACV targets. Frequent travel and Texas residency are required.

Lead and manage consulting engagements delivering power market analysis, price forecasts, asset valuations, transaction support, and strategic advisory. Oversee modeling (PROMOD, PSLF, PLEXOS, Aurora), mentor staff, manage client relationships, drive business development, publish thought leadership, and contribute to proprietary forecasting and analytical tools across U.S. power markets and technologies including renewables, storage, transmission, and large loads.