Top Machine Learning Jobs in Baltimore, MD

Apply machine learning to large datasets to build predictive models, perform data mining, and develop algorithms. Analyze results, create visualizations, and provide insights to inform business decisions.

The Senior AI/ML Engineer will work on government-related software, utilizing machine learning frameworks, data analysis, and algorithm design to improve AI and ML systems, while also overseeing integration processes and model validation.

Design, build, and deploy production-grade AI/ML systems (LLMs and agents) for Defense and Intelligence clients. Implement scalable MLOps, integrate models with cloud and APIs, evaluate LLM performance, and design robust service-based architectures while meeting security clearance requirements.

Lead architecture, design, development, deployment, and optimization of an agentic AI platform. Partner with product, data, security, and business teams to productionize AI solutions, establish engineering best practices, mentor teams, and drive reusable AI services, automation, and operational improvements to deliver business impact.

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

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

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 VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven 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.

As a GTM Engineering Intern, you will automate workflows, design demos, and develop AI-powered tools for market outreach while collaborating with sales and engineering teams.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

The Customer Success Manager drives the adoption of AI solutions in life sciences by managing implementations, developing customer satisfaction strategies, and serving as a trusted advisor.

Two research fellows will receive a stipend and compute credits to pursue projects in legal AI and automated negotiation. Fellows get expert access, private contract data, and are expected to produce a publishable paper, benchmark, or open-source artifact. Research topics include reward modeling under expert disagreement, negotiation simulation, minimal-diff editing benchmarks, uncertainty/hand-off strategies, or related legal AI problems.

Lead vision, strategy, and roadmap for pricing platforms, owning internal Rating Plan Manager and tooling to speed model deployment, improve workflow reliability and observability, enable self-service experimentation, and support regulatory/state-level pricing needs through cross-functional collaboration.

Lead development and implementation of machine learning and generative AI solutions for retail/CPG data. Perform customer, product, and transaction-level analysis, build models and simulation applications, create Tableau visualizations, write SQL (BigQuery) and Python ETL, ensure data quality, work with client stakeholders, and mentor junior analysts.

Hands-on analytics role building and maintaining ML and generative AI models for retail/CPG datasets. Conduct descriptive and customer/product/transaction-level analysis, create Tableau dashboards, write SQL (BigQuery) and Python data workflows, design LLM embedding solutions, build simulations, ensure data quality, work with senior stakeholders, and mentor junior team members.

Lead statistical activities for clinical trials from protocol design through reporting. Provide statistical oversight, collaborate with cross-functional teams and CROs, apply SAS/R (and ML) for analyses, automate processes, and mentor junior statisticians.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

Lead engineering strategy and delivery for customer-facing web and mobile platforms; drive AI-native transformation, increase conversion and speed-to-fund, raise engineering talent and velocity, ensure secure and compliant architectures, partner with product and cross-functional teams to deliver measurable business outcomes.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

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.

Lead architecture and development of a SaaS platform for data center energy procurement. Build forecasting, contracting, and monitoring modules; implement AI tools on AWS (Bedrock, SageMaker); hire and mentor engineers; translate business logic into scalable systems; deliver demos to investors and customers.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.