Top Senior Machine Learning Jobs in Richmond, VA

Lead and develop a team of five East Coast Enterprise Sales Leaders to drive new logo acquisition and account expansion. Build sales plans, manage pipeline from lead generation through close, recruit and coach leaders, and contribute to GTM strategy while reporting to the VP of Enterprise Sales. Remote-first role with occasional off-hours work.

Lead and manage actuarial projects for healthcare clients, provide technical and strategic actuarial advice, build financial models, mentor junior actuaries, and support practice development and client relationships to drive financial decision-making.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Lead product vision and roadmap for Tekion's Automotive CRM, translate dealer and partner needs into product requirements, define AI/LLM-enabled CRM capabilities, collaborate cross-functionally to deliver SaaS CRM features, create product artifacts, measure success metrics, and prioritize initiatives to drive adoption and strategic account success.

Build and maintain ML and generative AI tooling, training and inference platform services, model evaluation and testing frameworks, and APIs to expose ML products. Deploy and manage applications across the AI/ML SDLC, mentor teammates, and write production-quality code daily.

Lead enterprise AI platform automation across infrastructure provisioning, CI/CD, governance, observability, deployment, and lifecycle management. Build self-service capabilities for GenAI, data science, data engineering, and analytics workloads using Terraform, Kubernetes, cloud technologies, Python, and DevSecOps practices. Support agentic AI, event-driven architectures, distributed computing, and operational reliability while collaborating with engineering, architecture, governance, security, and business stakeholders. Provide technical leadership, design reviews, mentoring, and best-practice guidance.

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.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Lead design, build, and operation of data architecture, pipelines, and semantic layers. Manage sprint planning, DevOps metrics, data quality and monitoring, and MLOps enablement. Partner with stakeholders, coach engineers, track project plans, and ensure data availability, accuracy, and documentation.

Lead strategy and build 0->1 AI products that streamline complex healthcare workflows across providers, pharmacies, patients, and pharma partners. Own roadmap, requirements, metrics, and product performance; partner with engineering, data, clinical, and commercial teams to launch and iterate AI-enabled solutions that drive adoption and measurable business and patient outcomes.

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

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.

Lead end-to-end product areas that improve build speed, cost accuracy, margin, and throughput. Own strategy, roadmap, and execution for complex financial and operational data products, integrate AI/ML into workflows, write precise requirements, instrument metrics, run experiments, and drive cross-functional outcomes with construction, finance, sales, design, and engineering teams.

Lead the Contracts product roadmap for a B2B healthcare SaaS platform, applying deep reimbursement and managed care expertise. Partner with AI engineers to build contract-understanding models, drive adoption, iterate on workflows, create business cases, and coordinate cross-functionally with Legal, Finance, Sales, and SMEs to ensure compliant, revenue-aligned contract execution.

Lead engineering team to define and execute threat detection, platform, analytics, and automation roadmaps. Advance automated, AI-augmented detection and response across SIEM/EDR/NDR/SOAR and cloud environments, partner with Incident Response, and drive measurable risk reduction via metrics and team development.

Design, develop, and productionize scalable machine learning and data science solutions for clients. Analyze very large datasets across cloud platforms, implement recommender/NLP/computer vision and LLM-based systems, optimize for performance and scalability, leverage containerization and data warehousing, and lead/mentor junior practitioners while supporting business development and client strategy.

Lead design and delivery of end-to-end, production-scale ML systems on cloud platforms. Provide technical leadership, mentor teams, analyze and transform large datasets, implement recommender/NLP/risk models, productionize scalable ML, and grow practice through client-facing activities and business development.

Embed with customers to discover needs, design and implement production-grade integrations (APIs, data pipelines, event-driven workflows), deploy and troubleshoot solutions, train IT teams, and drive adoption and measurable business outcomes.

Own end-to-end computer vision and machine learning projects for power grid infrastructure, from problem framing and research experimentation through production deployment and monitoring. Develop detection, segmentation, classification, anomaly detection, and foundation-model solutions; build data pipelines, serving systems, experiment tracking, and model versioning. Conduct error analysis, benchmarking, tuning, code reviews, and testing while translating client requirements into reliable production models and communicating technical decisions and limitations.

Build and improve machine learning systems for ad ranking, relevance, and optimization. Responsibilities include developing active learning and LLM-assisted labeling workflows, owning experimentation and evaluation, and deploying low-latency inference services. The role partners with product, data, and platform teams to improve advertiser performance and user engagement while ensuring production reliability, scalability, latency, and data quality. Candidates will use Python, Go, AWS, distributed systems, and AI-assisted development tools.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.