Top Remote Machine Learning Jobs in Baltimore, MD

Lead Pearl's Enterprise AI product business end-to-end: define vision and GTM, build and scale AI+human offerings, partner with enterprise customers, and run a lean cross-functional team to deliver measurable commercial outcomes.

Senior individual-contributor role leading 3Cloud's enterprise AI strategy and Center of Excellence. Advise C-suite clients, define AI architectures and standards, drive adoption, develop offerings, and convert strategy into implementation while mentoring technical leaders and shaping commercial growth.

Lead enterprise AI and transformation engagements—own customer relationships, scope buildable solutions with FDE, drive commercial outcomes and expansion, advise C-suite on AI strategy, and create repeatable, scalable offerings to evolve Tive into an AI-powered intelligence platform.

Lead vision, strategy, and execution to modernize the WinTeam ERP platform. Drive AI-first workflows, roadmap prioritization, and technical modernization. Build and mentor a high-performing PM team, align stakeholders across Engineering, Design and GTM, deepen customer engagement, and deliver data-driven ROI and product profitability.

Design, build, and operate hyperscale Azure availability and control-plane services to achieve high VM SLAs. Lead architecture, author designs, implement reliable code, run livesite as DRI, and integrate predictive ML/AI models and generative AI for diagnostics and automated root-cause analysis.

Support design, development, and implementation of a CMS-focused data warehouse program. Analyze and validate complex datasets, perform ad hoc and predictive analyses (including ML/fraud analytics), produce reports and metrics, provide QA and technical guidance, and streamline data processes using Excel, Power BI, Tableau, and SharePoint.

Design, build, and maintain ETL pipelines and data quality processes to support CMS fraud, waste, and abuse detection. Analyze structured and unstructured data, implement data validation, develop dashboards and QA reports (Excel, Power BI, Tableau), collaborate with product and DBA teams, perform ad-hoc and statistical analyses, and participate in Agile ceremonies.

Lead development and optimization of prompt engineering strategies and RAG frameworks. Build Python-based AI applications using Azure OpenAI and AWS, manage AI project delivery, optimize ML models, and collaborate with cross-functional teams to integrate cloud-based AI solutions following Agile methodologies.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Lead development of safety frameworks and V&V for end-to-end autonomous robotics, perform risk assessments and safety reviews, derive technical safety requirements, and coordinate cross-functional teams to monitor fleet performance and deploy scalable autonomy.

Lead strategy and execution for AI-powered Customer Success Services, overseeing Gainsight and related platforms, customer community strategy, customer intelligence, automation, digital engagement, platform governance, and a team to scale adoption, retention, and operational efficiency across the customer lifecycle.

Develop and implement AI solutions, optimize models, preprocess data, integrate AI into workflows, and collaborate with cross-functional teams.

Lead and execute statistical and geospatial analyses to quantify and map climate mitigation potential from forests and peatlands. Design analytical workflows, manage projects and partners, create datasets, tools, reports, and deliver trainings and technical support for global conservation initiatives. Communicate results via publications, visualizations, and capacity-building activities; occasional fieldwork and international travel possible.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

Develop and execute test strategies for data pipelines, integrations, ML models, and applications to ensure clinical data quality. Create/maintain test data and environments, automate tests, run system/UI/integration testing, report results, assess risk, and collaborate with cross-functional Agile teams to improve testing practices.

Lead enterprise solution architecture for the CMS HIGLAS/HOM program: define multi-year roadmaps, modernize Oracle ERP (EBS, Hyperion) across OCI and hybrid clouds, design integrations and AI/ML analytics pipelines, ensure security/compliance (HIPAA, FedRAMP), oversee data migration and HA/DR, run architecture reviews, and mentor teams through delivery and transformation.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.