Top Senior Machine Learning Jobs in Baltimore, MD

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Owns BI product strategy for Quote-to-Cash and Order-to-Cash financial systems. Builds relationships with finance and FinSys stakeholders, identifies BI and AI/ML opportunities, writes PRDs and roadmaps, defines business requirements, and partners with engineering teams. Ensures quoting, deal structuring, billing, revenue recognition, pricing, order, and contract data are accurately represented in downstream data products and dashboards.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Leads market strategy, positioning, messaging, product launches, go-to-market execution, sales enablement, thought leadership, and customer insight programs for Lumana’s AI video security platform. Partners cross-functionally with Product, Engineering, Sales, Marketing, and Customer Success to influence roadmap priorities, align teams, strengthen competitive differentiation, and drive measurable business outcomes in a high-growth startup environment.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead client AI transformation engagements from discovery through implementation. Develop AI strategies and roadmaps, apply product management practices to prioritize and deliver solutions, collaborate with engineering and data teams, participate in Agile delivery, mentor consultants, support business development, and ensure successful, timely delivery of AI and analytics solutions.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

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

Analyze complex national security missions and operational environments; develop strategic frameworks, visualizations, exercises, and wargaming approaches. Assess AI and ML capabilities, including risks, vulnerabilities, and adversarial factors. Integrate data feeds, create dashboards, conduct capability assessments, collaborate with industry and academia, and prepare executive recommendations and briefings for senior leaders.

The role includes advising on AI compliance, assessing regulatory risks, establishing governance, and collaborating with various teams on AI initiatives in Wealth Management.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

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.

Develop full-stack software and web applications for national security customers. Translate mission needs and user requirements into maintainable, user-friendly systems using strong Java and JavaScript/TypeScript skills. Apply continuous integration, collaborate through design discussions and documentation, adapt to changing customer needs, meet deadlines, and support mission requirements within a geographically distributed engineering team.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Own the full enterprise sales cycle for Oversee’s leisure travel business, from prospecting through closing. Build relationships with OTAs, agencies, tour operators, and vacation providers; develop pipeline; identify target segments and use cases; refine positioning and sales strategy; lead complex stakeholder processes; and partner with Product and Engineering to convert market insights into a repeatable leisure sales motion.

Own AgentSee’s sales and go-to-market strategy as the first dedicated sales leader. Personally close early enterprise opportunities, refine the ideal customer profile, positioning, pricing, packaging, and sales process, and translate AI capabilities into measurable business value. Build repeatable sales operations and playbooks, provide market feedback to Product and Engineering, and eventually hire and lead the AgentSee sales organization.

Own customer onboarding by prioritizing integration work, developing Python and SQL data pipelines, automating repetitive processes, and leading technical customer calls. Translate CRM and fundraising data into model-ready formats, manage onboarding risks, document processes, support CSMs, and train team members. The role serves as Dataro’s US technical customer representative while collaborating with engineering in Sydney.

Owns the design, development, optimization, and lifecycle management of Tableau dashboards, data products, and procurement reporting solutions. Analyzes spend, sourcing, supplier, contract, and accounts payable data; translates findings into recommendations; supports Tableau Server governance; and enables self-service analytics. Partners with procurement and cross-functional stakeholders, presents insights to senior leaders, and evaluates AI-enabled opportunities to improve business outcomes.

Senior-level engineer delivering analytics and ML-Ops solutions for healthcare payers. Design and implement analytics platforms on Databricks, develop CI/CD and provisioning patterns, collaborate with data scientists, mentor juniors, and build client relationships to drive actionable insights and operational improvements.

Develop computer network operations capabilities across full project life cycles. Lead Agile teams conducting reverse engineering and vulnerability analysis, develop complex Windows and UNIX applications, and manage software design, development, testing, validation, and deployment. Apply embedded development, network operations expertise, and artificial intelligence and machine learning to address advanced adversaries and support national security missions.