Top Remote Machine Learning Jobs in Houston, TX

Lead strategy and execution for AI-powered Customer Success Services, overseeing Gainsight and related platforms, customer community strategy, customer intelligence, automation, digital engagement, platform governance, and a team to scale adoption, retention, and operational efficiency across the customer lifecycle.

Develop and implement AI solutions, optimize models, preprocess data, integrate AI into workflows, and collaborate with cross-functional teams.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

The role involves conducting research and optimizing machine learning systems while collaborating with technical staff to enhance product performance.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.

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 Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

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.

The Research Advisor will provide high-level consultancy for generative AI systems, engage in research collaborations, and represent the Human Frontier Collective in key executive meetings.

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

Full-cycle quota-carrying Account Executive selling Bold Metrics' SaaS fit and sizing solutions to apparel brands. Own outreach through contracting, build ROI cases, manage cross-functional coordination, develop outbound strategies, leverage AI to scale workflows, track funnel metrics, and feed customer insights to Product.

Lead and mentor full-stack engineering teams to design, build, test, deploy, and support scalable client-facing and proprietary software. Drive architecture, technical roadmap, Agile delivery, cloud-native migrations, API integrations, quality metrics, and cross-functional collaboration while balancing hands-on development and people leadership to meet product and business goals.

Pre-sales technical role: demonstrate Kore.ai platform, architect and whiteboard solutions, run use-case workshops, estimate ML effort, collaborate with product and delivery teams, and support sales to close enterprise AI and contact-center deals.

Own a Pod's product roadmap: discover customer problems, define initiatives, write high-level requirements, partner with engineering, integrate AI-driven workflows, ensure adoption, track outcomes, and steward product metrics.

Lead pet insurance pricing and state rating plans; build and integrate ML rating models; design pricing strategy for expansion; support rate filings; partner with Data Science, Underwriting, and Finance; and manage and grow an actuarial analyst team.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.

Own and scale Root's largest enterprise partnerships (OEMs, financial institutions, dealer groups). Drive account strategy, manage a $100M+ pipeline, identify and close new business, lead executive negotiations and contract execution, coordinate cross-functional launches, monitor partnership health, and influence product and commercial strategy to deliver growth.

The Senior ML Engineer will develop and deploy full-stack AI solutions, manage LLM integration, and collaborate closely with defense clients to enhance real-world applications in secure environments.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Build and productionize AI systems for logistics: multi-agent copilots, forecasting/optimization models, evaluation and observability, continuous learning loops, and operational reliability. Mentor engineers and make build-vs-rule tradeoffs while shipping high-impact ML services.

Define and execute predictive modeling and ML strategy for credit risk, servicing, and collections. Lead cross-functional initiatives, oversee model development, deployment, and monitoring, advise senior leadership on data strategy, represent analytics in regulatory and audit forums, and mentor peers while fostering organizational partnerships.

Lead and execute ML/AI strategy, design and deploy production-grade ML and GenAI solutions, mentor MLEs, collaborate with cross-functional teams, and build scalable, secure ML/LLM platforms and inference pipelines to drive business impact.