Top Remote Machine Learning Jobs in Baltimore, MD

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.

Lead and grow a platform engineering team responsible for ML training and serving. Define roadmap, drive execution, ensure reliability, optimize GPU and deployment infrastructure, and collaborate with ML, product, and infra teams to support high-priority ML initiatives.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

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.

Design measurement frameworks and advanced causal inference solutions for marketplace allocation and recommendation systems. Partner with Product, Engineering, and business stakeholders to translate needs into scalable data science tools, run experiments, quantify impact, and drive implementation for Netflix discovery surfaces.

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.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

The role involves conducting research and optimizing machine learning systems while collaborating with technical staff to enhance product performance.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.