Top Senior Machine Learning Jobs in Richmond, VA

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.

Lead planning, execution, and optimization of cross-functional hardware and software projects for robot development, manufacturing, testing, upgrades, and deployments. Coordinate mechanical, electrical, embedded, systems, manufacturing, and operations teams, define scope and timelines, mitigate risks, implement process improvements, run sprints, and maintain project documentation and stakeholder communication.

Lead Woolpert's partner marketing for the Google relationship: develop and execute joint go-to-market plans, run integrated campaigns, enable sales, create partner collateral, measure KPIs, and coach one specialist to drive co-selling and pipeline growth for Digital Innovations.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Build and own end-to-end product features across React/TypeScript frontend, Ruby on Rails backend, relational databases, and GCP/AWS infrastructure. Partner with product, design, clinical, and operations teams to translate complex healthcare workflows into simple experiences. Improve reliability and performance, mentor engineers, raise engineering standards, and integrate AI-powered features into production.

Lead statistical design and analysis for Phase I-IV clinical studies, develop protocols and SAPs, perform efficacy and exploratory analyses, run simulations, apply advanced methods (mixed models, longitudinal), oversee datasets (ADaM/CDISC), use R and SAS for analyses, and provide strategic statistical guidance to cross-functional teams supporting regulatory submissions.

Lead and grow a team of 5-7 enterprise sales reps in the Bay Area, recruit and develop sales leaders, build business plans, drive new-logo acquisition and account expansion, manage the sales cycle from lead generation to close, develop GTM strategy, and report to the VP of Sales. Role supports ambitious quarterly and annual goals and may require occasional work outside standard hours.

Lead the vision and execution of data product roadmap; translate business needs into epics and acceptance criteria; partner with data engineering and analytics; run agile ceremonies and manage backlog; champion data-as-a-product; scope and pilot AI/ML capabilities; present roadmaps and business cases to leadership.

Sell Fiddler’s AI observability platform to enterprise customers: prospect, navigate complex multi-stakeholder deals, demonstrate technical and business value for ML/AI solutions, close revenue, grow accounts, and collaborate cross-functionally. Travel as needed (10–25%).

Full-cycle territory sales role selling Greenway Health's EHR, RCM, and AI-driven healthcare solutions. Responsibilities include prospecting, lead generation, demos, RFP management, proposal configuration, negotiation, closing, maintaining Salesforce, meeting quota, and providing market feedback. Role requires heavy travel (50–75%) and collaboration with internal solutions consultants to deliver value-based technology and revenue cycle capabilities to ambulatory healthcare clients.

Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.

Lead and scale end-to-end data annotation operations: set quality standards, build and manage an in-house annotation team and vendors, translate research into annotation guidelines, implement QA systems, drive AI-assisted labeling, partner with ML/CV and product, and own metrics and reporting.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Own end-to-end product development for AI/ML revenue cycle solutions: define vision and roadmap, write specs and user stories, prioritize backlog, work closely with data scientists and engineers, drive agile delivery, ensure quality, and measure product performance with stakeholders.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Technical Product Marketing Manager will drive product marketing strategy, understand Socure's technology, craft technical narratives, and enhance internal and external communication through enablement materials.

Provide legal counsel on privacy, AI, identity, and advertising technology; embed privacy by design with product and engineering teams; draft and negotiate privacy provisions and DPAs; advise on cross-border transfers and SCCs; run privacy and AI risk assessments; support incident response; create scalable legal playbooks and AI-enabled workflows; represent Yahoo in industry standards bodies.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.

Design and develop advanced machine learning and generative AI solutions for complex business problems. Build, fine-tune, evaluate, optimize, and deploy LLM and ML models using AWS services, SageMaker, RAG architectures, vector indexing, and MLOps practices. Create scalable end-to-end architectures for training, inference, retraining, and web application integration. Collaborate with developers, QA, project managers, and stakeholders to deliver reliable AI solutions.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Lead product ownership for Advisor Experience, owning roadmap from discovery to delivery. Build integrations and AI features (Aspen AI, client portal), deliver advisor capacity and transition tools, work with engineering/design/data and external partners, and drive Client Excellence KPIs (Net Revenue Retention, NPS, advisor retention, transition success).