Top Senior Machine Learning Jobs in Richmond, VA

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.

Lead and scale a Card risk assessment team, drive transformation of assessment programs (PLA, RCSA, risk inventory), integrate AI/ML and data analytics for continuous risk insights, advise stakeholders and regulators, and develop talent while improving processes and cross‑functional alignment.

Own the transition of AI/ML models from experimentation to reliable production deployment. Build scalable infrastructure, automation, and CI/CD workflows; implement monitoring, dashboards, drift detection, experiment tracking, and model versioning. Collaborate with data scientists and AI researchers, while managing cloud environments and GPU resources for scalable, cost-effective operations. The role requires onsite work in Dallas, Texas.

Develop and improve predictive pricing models using statistical and machine learning techniques. Apply feature engineering to complex datasets, incorporate new data sources, design controlled experiments, and communicate insights to senior leaders. Research data science innovations, contribute to the modeling capability roadmap, and explain model functionality to technical and nontechnical stakeholders. Collaborate with analysts and systems experts to deploy models effectively.

Own BI product strategy for Quote-to-Cash and Order-to-Cash financial systems. Identify operational friction and translate it into BI, AI, and machine learning opportunities. Create PRDs, roadmaps, and functional requirements while partnering with finance, sales, legal, product, technical delivery, and engineering teams. Ensure quoting, contracting, billing, revenue recognition, pricing, and order data are accurately represented in downstream data products and dashboards.

Develop and deploy production computer vision and machine learning models for object detection, segmentation, classification, video analysis, forecasting, anomaly detection, regression, and clustering. Translate business needs into scalable AI solutions, fine-tune architectures using PyTorch and TensorFlow, analyze model performance, and account for hardware and real-world constraints involving cameras, sensors, lighting, and edge devices.

Leads procurement governance, operating standards, project portfolio oversight, AI adoption, digital transformation, continuous improvement, executive reporting, financial analysis, compliance, and supplier performance initiatives. Establishes frameworks, KPIs, dashboards, workflows, and knowledge systems while coordinating procurement with facilities management and other operational stakeholders.

Design, build, deploy, and maintain production ML systems and data pipelines at scale. Lead cross-functional teams to implement ML architectures, ensure model performance and governance, automate CI/CD for models, and leverage cloud platforms and ML frameworks to deliver reliable, explainable solutions.

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.

Design, build, deploy, and maintain production-scale ML models and pipelines. Collaborate with cross-functional Agile teams to implement cloud-based architectures, optimize model performance, automate CI/CD, and ensure model governance, monitoring, and responsible AI practices.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

The Senior Lead Machine Learning Engineer will design, implement, and scale ML applications, ensuring performance and high availability while collaborating with cross-functional teams.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead design, build, deploy, and maintain production ML models and pipelines at scale. Collaborate with product and data science teams to architect cloud-based ML systems, automate CI/CD, monitor and retrain models, ensure model governance and explainability, and drive high availability and performance.

As Director of Product, you will define and drive Kobie's data platform strategy to enhance marketing and loyalty programs, focus on AI integration, and develop commercial models.

Develop and enhance predictive models for search and recommendations using large datasets, statistical methods, and machine learning. Incorporate new data sources, design controlled experiments, communicate insights to senior leadership, research emerging methodologies, and help shape the data science roadmap. The role also requires collaboration, project delivery, and explaining technical concepts to technical and non-technical audiences.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Lead and transform the Fraud Intelligence Team into a high-impact function by improving operating models, QA, tooling, and metrics; build entry-level talent programs; connect labeling to measurable fraud prevention outcomes; deliver actionable insights to Product, R&D, Analytics, and GTM; and leverage AI and automation to increase productivity and business impact.

Partner with functional leaders to translate business strategy into people strategy. Own org design, performance management, compensation, talent development, engagement, and retention. Provide coaching on career pathing, change management, and sensitive employee issues. Use people data to generate insights and recommendations, build compliant HR policies, manage global employee relations, and collaborate with People Team COEs to deliver cohesive people programs at scale.

Serve as second-in-command for Coinbase Derivatives' Market Regulation Department, leading day-to-day regulatory compliance, managing exams and audits, advising on CFTC Core Principles, reviewing surveillance escalations and enforcement actions, and coordinating cross-functional regulatory workstreams to ensure the DCM meets obligations and resolves findings timely.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Build and lead detection-as-code, AI/ML, automation, and response capabilities for a global security operation. Develop production AI/ML pipelines for investigation, triage, enrichment, and detection generation; establish version-controlled detection standards, testing, and CI/CD deployment across SIEM, XDR, and EDR platforms. Create SOAR workflows, response playbooks, and containment integrations. Maintain MITRE ATT&CK coverage, partner with threat intelligence and hunting teams, validate defenses through purple teaming and breach-and-attack simulation, and lead technical projects as the senior individual contributor.

Drives operational excellence through data analysis, dashboards, process improvements, and cross-functional project leadership. The role embeds with business units to manage day-to-day operations, investigate trends, answer strategic questions, implement workflows, coordinate stakeholders, track deliverables, and present insights to technical and non-technical audiences. It serves as a strategic partner to operations leadership in a fast-paced, ambiguous environment.