Top Senior Machine Learning Jobs in Houston, TX

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

Lead technical pre-sales and enterprise rollouts by owning infrastructure strategy, PoCs, migrations (on‑prem to cloud), DMS/CRM integrations, InfoSec discussions, and stakeholder engagement with C-level sponsors to enable scalable deployments and upsell opportunities.

As a Senior Data Scientist, you will identify business opportunities, build machine learning solutions, partner cross-functionally, and translate analyses into actionable insights.

The Solutions Architect will bridge customers and sales, ensuring the technical fit of software solutions, leading demos, and managing deployments effectively.

The Senior Manager will oversee the fraud lifecycle, optimize detection strategies, conduct fraud reviews, collaborate with teams, and manage risk reporting.

Design and build backend systems and APIs for AI-driven products, ensuring scalability, reliability, and integration of ML models while collaborating with engineering and product teams.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Lead design and scaling of a unified fraud and risk platform. Own roadmap, fraud metrics, SQL-based analysis, A/B testing, real-time detection models, and cross-functional delivery to balance customer experience and risk mitigation.

Lead analyses measuring campaign impact, build tagging models (prompt engineering and ML), synthesize insights across programs, analyze experiments including RCTs, and produce presentations and post-campaign reports for internal teams and clients.

Lead North America revenue growth by building relationships, managing pipeline, responding to RFPs/RFIs, coordinating cross-functional teams, tracking activity in Salesforce, representing Optibus at industry events, and delivering data-driven sales forecasts.

The Machine Learning & AI Engineer develops and deploys ML and AI systems for the Energy Industry, focusing on data quality and interpretability. Responsibilities include model design, pipeline development, AI agent systems, and collaborating with cross-functional teams.

The role oversees analytical characterization and comparability studies for biologics, ensuring regulatory compliance and leadership in product development.

The Customer Solutions Manager will engage customers, lead solution adoption, coordinate with internal teams, and ensure customer success in telecom solutions.

The role involves developing and improving TTS/Voice Generation models, training, fine-tuning, evaluating speech models, and collaborating across research, engineering, and product teams in a fast-paced startup environment.

The Director leads compliance and business process governance, ensuring alignment with enterprise priorities, integration of compliance objectives, and drives operational effectiveness and innovation.

As a Staff Data Scientist, you will lead product strategy by building predictive models, optimizing matching algorithms, and guiding product innovations in a consumer tech environment.

The Business Development Director will lead strategic engagement with Google Cloud, focusing on partnership growth, go-to-market strategies, and revenue generation through cloud solutions.

The Business Development Director will lead strategic engagement with Oracle Cloud Infrastructure, focusing on alliance strategies, go-to-market execution, and revenue growth through innovative cloud solutions.

The VP of Product Development will lead a global engineering team for eDiscovery platforms, focusing on modernization, reliability, and AI integration while managing execution and stakeholder communication.

Lead a team of machine learning engineers and data scientists to develop algorithms for personalized shopping, enhancing client engagement and driving growth through AI and data science.

Lead the Prediction and Planning teams at Motional, overseeing machine learning initiatives, establishing technical roadmaps, and mentoring engineers. Publish research and collaborate across teams to integrate developments into vehicle platforms.

Lead the design and implementation of AI-driven fraud prevention strategies, balancing user experience with security to protect user data and prevent unauthorized access.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.