Top Remote Machine Learning Jobs in Houston, TX

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

The Strategic MSP/MSSP Account Executive will identify and develop partnerships, create strategic plans, and drive revenue growth by engaging with prospective MSP/MSSP partners while collaborating internally to optimize sales strategies and maintain relationships.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

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

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

Lead net-new enterprise sales in the Energy vertical: build pipeline, close complex deals, manage full sales cycle, collaborate with GTM for POCs, transition closed accounts to delivery teams, and relay market feedback to product. Role requires periodic travel and U.S. passport.

Responsible for bioinformatics ML/AI application development in clinical settings, designing and deploying ML/AI solutions, and collaborating with multidisciplinary teams.

Join the Growth team to own funnels that drive discovery, evaluation, and purchase of car insurance. Conduct product walkthroughs, synthesize user feedback, drive bug triage, lead end-to-end product initiatives, partner with Design/Engineering/Analytics to ship experiments and A/B tests, translate ambiguous problems into hypotheses and requirements, and coordinate daily overlap with a China-based engineering team to ensure execution.

Lead Jerry.ai's organic community strategy across Reddit, Quora, YouTube, and TikTok. Grow and moderate subreddits, create scalable authentic content and engagement playbooks, collaborate with Growth and Content, and measure community metrics like sentiment, share of voice, referral traffic, and LLM citation.

Join Growth as a Product Manager to map user journeys, monitor feedback, triage bugs, and lead end-to-end product initiatives. Partner with Design, Engineering, Analytics, and Marketing to run A/B tests, analyze funnels, translate customer problems into hypotheses and requirements, and coordinate daily overlap with a China-based engineering team to ensure tight execution.

Join the Growth team to map user journeys, synthesize user feedback, triage bugs, and lead end-to-end product initiatives. Partner with Design, Engineering, Analytics, and Marketing to run A/B tests, analyze funnels, translate customer problems into hypotheses and requirements, and coordinate daily overlap with a China-based engineering team to ensure execution.

Owner of growth funnels for car-insurance product discovery and purchase. Map user journeys, synthesize feedback, triage bugs, run A/B tests and funnel analysis, and lead end-to-end launches while coordinating with design, engineering (China overlap), analytics, and marketing to drive experiments and product improvements.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

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.

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.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

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

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

Lead zero-to-one product initiatives to transform knowledge discovery using ML/LLMs. Define vision, roadmap, and success metrics; prioritize trade-offs; partner with Design, Engineering, ML, and Data Science; deliver incremental wins while building an extensible platform and improving prospect and subscriber experiences across devices.

Lead pre-sales engagements by demonstrating Snowflake value, running proofs of concept, designing solutions, partnering with sales and product teams, and closing large enterprise deals while advising on data architecture and AI/ML deployments.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.