Top Machine Learning Jobs in Baltimore, MD

Develop and maintain quantitative models for forecasting, pricing optimization, and risk assessment. Analyze mortgage business metrics to identify revenue, profitability, and operational improvement opportunities. Build performance measurement frameworks, dashboards, automated reports, and SQL-based analytics workflows. Use Python for statistical analysis, automation, and machine learning workflows. Validate and monitor model performance, recalibrating models as needed, while communicating actionable recommendations to business leaders.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Designs, develops, tests, deploys, trains, monitors, and improves machine learning models for business and national security mission requirements. Responsibilities include selecting datasets, statistical analysis, algorithm execution, model evaluation, data pipeline integration, system testing, and scalable solution development. The role requires strong understanding of AI/ML architectures, application development, infrastructure, data engineering, and governance, with potential leadership of distributed teams.

Analyzes, designs, develops, and maintains Java-based eCommerce systems, web applications, payment-processing integrations, APIs, and distributed infrastructure. The role also builds AI and machine-learning tools for transactional and operational data analysis. Responsibilities include architecture evaluation, performance tuning, security and PCI DSS compliance, testing, documentation, CI/CD maintenance, troubleshooting, and Agile collaboration.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Leads analytical and scientific strategy for Fetch’s Play and Rewarded Apps businesses. Develops predictive and machine learning models, experimentation frameworks, causal analyses, feature pipelines, and measurement systems using Python and SQL. Partners with Product, Marketing, Engineering, and business leaders to improve monetization, engagement, retention, personalization, and marketplace outcomes. Translates complex findings into strategic recommendations, mentors data scientists and analysts, and establishes analytical best practices.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own the full machine learning lifecycle for search ranking and retrieval, including model training, deployment, serving, feature pipelines, evaluation frameworks, hybrid lexical-vector retrieval, large-scale embedding inference, query understanding, and permissions-aware multi-tenant search. Collaborate with infrastructure, AI, and backend teams to improve search relevance across ClickUp’s platform.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

Senior backend engineer responsible for setting technical direction, designing scalable distributed systems, building customer-facing web applications, mentoring engineers, and applying machine learning to large-scale healthcare data. The role requires Java, Scala, or Rust expertise, cloud systems experience, technical design leadership, cross-functional collaboration, and adoption of agentic engineering practices.

Leads Alkami’s enterprise and technology risk management program, including risk assessments, control evaluations, mitigation, monitoring, reporting, and escalation. Owns AI, machine learning, and generative AI governance, translating regulatory and risk expectations into practical policies, controls, and review processes. Partners with cross-functional risk owners and supports compliance initiatives involving business continuity, disaster recovery, regulatory management, and incidents. Reports to the Chief Compliance Officer in a fully remote role.

Build and operate production retrieval-augmented generation systems, including embeddings, vector retrieval, grounded language-model generation, citation validation, prompt and schema design, model packaging, serving, rollback, and telemetry. Develop bounded model assistance for narrative extraction with provenance and rule-context tracking. Maintain resilient serving paths in secure government cloud environments, including restricted or air-gapped deployments.

Provides product and technology legal counseling throughout the product lifecycle while operating Horizon3’s global privacy program. Advises Product, Engineering, Security, Compliance, and GTM teams on privacy laws, AI regulation, data flows, DPAs, cross-border transfers, privacy-by-design, incidents, audits, and customer diligence. Drafts playbooks, policies, notices, and contractual terms; supports enterprise negotiations; and delivers practical, risk-based guidance in a fast-moving cybersecurity environment.

Build and productionize machine learning systems that convert complex documents into executable, verifiable logic. Responsibilities include developing parsing and transformation pipelines, experimenting with language models, designing datasets and evaluation metrics, creating adversarial tests, analyzing model failures, and implementing rule-based checks using logical reasoning and program analysis. The role requires close collaboration with founders and subject-matter experts to validate system outputs.

Leads large-scale AI transformation programs for Cresta’s strategic enterprise customers. Serves as executive sponsor and trusted advisor to C-suite stakeholders, manages matrixed implementation and engineering teams, oversees complex deployments, standardizes delivery governance, and drives measurable customer value, adoption, expansion, and advocacy. Partners with Sales, Customer Success, Product, and Engineering while connecting technical outcomes to business ROI.

Develop and integrate cloud software, AI/ML capabilities, distributed analytics, and microservices on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, cloud deployment, testing, troubleshooting, RESTful services, Hadoop-based big-data processing, infrastructure as code, CI/CD, and Linux systems work. The role requires active TS/SCI clearance with polygraph and one approved cloud developer certification.

Develop and sustain cloud software for cyber intelligence and AI/ML capabilities. Responsibilities include requirements analysis, Java development, distributed systems, cloud deployment, software integration, testing, troubleshooting, analytics development, and technical documentation. The role uses AWS, Kubernetes, infrastructure-as-code, CI/CD, Hadoop technologies, Linux, microservices, LLMs, and RAG frameworks while supporting large-scale data processing and national security missions.

Develop and sustain cloud software for national security missions, including requirements analysis, integration, testing, validation, and issue resolution. Build AWS-based services and distributed systems using Java, Kubernetes, infrastructure-as-code, CI/CD, Linux, and microservices. Integrate AI/ML capabilities, LLMs, and RAG frameworks while supporting large-scale compute clusters, big-data technologies, RESTful services, and cloud security practices. The role requires active TS/SCI clearance with polygraph and collaboration in a mission-driven cyber intelligence environment.

Designs and implements AI-enabled workflows for cyber and intelligence missions, including LLM-based agents, multi-step automation, API and data-store integrations, and production deployments in classified environments. Collaborates with mission users, analysts, developers, and leadership to translate operational workflows into reliable, secure capabilities. Requires Python experience, TS/SCI clearance with polygraph, and relevant AI/ML or software engineering experience.

Design, develop, test, deploy, and maintain scalable AI/ML and full-stack software using Java and Python. Customize LLM interfaces, integrate external requirements tools, troubleshoot defects, conduct code reviews, support planning, design accessible user interfaces, and mentor junior engineers. The role requires collaboration with customers, product managers, developers, subject matter experts, and leadership in a classified Intelligence Community environment.

Owns strategy, roadmap, lifecycle, metrics, responsible AI practices, commercialization, and go-to-market for AI/ML-powered healthcare products. Partners with Data Science, Engineering, Legal, Marketing, Sales, and customers to define use cases, requirements, success criteria, pricing, and launch plans. The role requires managing platform and partner integrations, coordinating cross-functional dependencies, ensuring HIPAA and privacy compliance, and translating technical AI concepts for business stakeholders.

Lead strategy and execution for enterprise and mid-market GTM across multi-unit restaurant brands. Drive C-suite engagements, modernize sales motions, scale AI-powered forecasting, partner with Product/Engineering, and represent Toast in industry forums to win large, complex contracts.

Own the machine learning and applied AI layer of a software platform, from research through production. Build text-processing pipelines, extract structured data from technical documents, develop LLM-powered decision workflows, create evaluation systems, and build NLP classifiers. Lead exploratory research, translate findings into product features, and collaborate with a small engineering team. The role is remote in the US or Canada, with quarterly travel.

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.

Develop and integrate AI/ML capabilities into operational software, including large language models, retrieval-augmented generation, agentic workflows, prompt engineering, and inference pipelines. Evaluate, test, document, and communicate AI system performance, reliability, design decisions, and technical contributions. Preferred experience includes secure development, DevSecOps, Kubernetes, OpenShift, CI/CD, containerized delivery, and classified or regulated environments.