Top Remote Machine Learning Jobs in Houston, TX

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Senior BI Data Researcher will lead research and engineering across modern data systems: big data management, data cleaning, quality, metadata, search/discovery, information extraction, time-series and heterogeneous analytics, applied AI/ML, distributed processing, and query/storage optimization. Collaborates with research teams to build scalable tooling, ML models across diverse modalities (tabular, time series, text, audio, video), and edge-enabled architectures.

Lead and scale the Emerging Technology program, driving adoption of generative AI, ML, and data science across the company. Oversee program strategy, budget, vendor selection, compliance with SOX/FFIEC, metrics, and pilot governance. Advise senior leadership, deploy ML frameworks (TensorFlow, PyTorch, SageMaker, Azure ML), build data-driven products, and ensure secure, ethical, and enterprise-scale implementations.

Design measurement frameworks and advanced causal inference solutions for marketplace allocation and recommendation systems. Partner with Product, Engineering, and business stakeholders to translate needs into scalable data science tools, run experiments, quantify impact, and drive implementation for Netflix discovery surfaces.

Lead and support full-lifecycle data science projects (forecasting, NLP, classification/regression, optimization). Design production-ready solutions within client environments, consult with stakeholders to define ambiguous problems, communicate technical findings, and develop/teach bespoke analytics training.

Lead vision, strategy, and roadmap for pricing platforms, owning internal Rating Plan Manager and tooling to speed model deployment, improve workflow reliability and observability, enable self-service experimentation, and support regulatory/state-level pricing needs through cross-functional collaboration.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Lead technical direction and deliver large-scale ML platform infrastructure including feature store, model serving, experimentation, and training pipelines. Drive architecture, mentor engineers, coordinate cross-team initiatives, resolve system-wide issues (latency, reliability, GPU utilization), and define safe ML deployment paths from registration through rollout, monitoring, and rollback.

Lead development and operationalization of a clinical reasoning framework for trustworthy clinical AI. Partner with product, engineering, editorial, and design to define decision pathways, evaluation benchmarks, validation protocols, and ongoing expert review. Translate clinical feedback into AI system improvements, represent the team externally, and optionally maintain limited clinical practice.

This is an open talent‑community posting inviting U.S.-based candidates across multiple disciplines (software, AI/ML, XR, UX/UI, DevOps, cybersecurity, data, instructional design, etc.) to submit a resume and brief introduction. HTX Labs will retain candidate information for future contract-to-hire opportunities. Must be authorized to work in the U.S.; no visa sponsorship available. Remote-first role supporting immersive learning for Department of Defense clients.

Design, develop, and deploy machine learning models and pipelines to optimize operations. Lead full ML project lifecycle, ensure model evaluation/monitoring, collaborate cross-functionally, mentor junior engineers, and drive continuous improvement in ML applications and processes.

Senior individual-contributor sales role responsible for hunting net-new consulting engagements across Data, Analytics, and AI. Build pipeline, originate opportunities, manage full sales lifecycle (prospect to signed SOW), engage senior executives, develop value propositions, and partner with technical and delivery teams. Focus on manufacturing and supply chain use cases, modern data platforms, enterprise integration, and ecosystem partners. Travel as needed to develop relationships and close deals.

Drive Midwest SLED revenue by selling analytics-driven SaaS identity and fraud solutions. Build pipeline, manage full sales cycle, develop partnerships/channels, collaborate with product, forecast accurately, and travel up to 50% to close deals and ensure customer success.

Lead product vision and execution for tDesign, an internal platform for small-molecule drug discovery. Define roadmap, translate complex AI/ML and scientific needs into intuitive UX, integrate AI agents and automated workflows, coordinate cross-functional teams, and drive adoption and product impact metrics.

Lead portfolio-level Data & AI strategy and technical governance for enterprise clients. Advise C-suite, drive architecture and modern data stacks, win high-value engagements, and scale engineering and data science teams.

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

Serve as the technical lead in pre-sales for state, local, and education customers: run discovery, design POCs and workshops, deliver demos, map needs to Socure solutions, advise on fraud/risk/compliance, influence product, and mentor junior consultants.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

Lead end-to-end deployments of AI for hotel revenue teams: integrate PMS/CRS/RMS, ship ML/optimization models and agentic workflows, validate recommendations with revenue managers, define metrics, drive adoption, and hire/mentor the forward deployed engineering team.

Lead strategy, roadmap, and lifecycle for payer analytics and automation products. Translate market, customer, regulatory, and data insights into product requirements, drive cross-functional delivery with Engineering and Data Science, support go-to-market and adoption, and measure product performance to inform investment and portfolio decisions. Build product practices and partner with stakeholders across sales, customer success, clinical, actuarial, and executive teams.

Lead Growth Engineering architecture and implementation: build Go-based data pipelines, audit/replace martech, create experimentation infrastructure, ship full-stack Go/TypeScript features, productionize ML, review team work, and apply AI-assisted development daily.

Lead and grow a team of 5–6 product developers to deliver high-quality, reliable software. Partner with product and design, champion CI/CD, testing, observability, and provide visibility to leadership while hiring and mentoring engineers.

Lead complex enterprise sales of AI-powered SaaS solutions, build pipeline, manage 6–12 month high-six-figure deals, multi-thread across stakeholder teams, collaborate with marketing/product/customer success, and translate technical AI capabilities into business ROI.

The Sales Engineer will lead the technical lifecycle of network solutions for customers, including requirements discovery, deployment, and optimization. They will provide technical oversight and collaborate with sales and engineering teams to ensure tailored solutions meet customer needs.