Top Machine Learning Jobs in Baltimore, MD

Administers Oracle, SQL Server, and Sybase databases supporting cloud-based AI/ML and national security systems. Responsibilities include database security, integrity and availability; user account management; disaster recovery; performance analysis and tuning; index maintenance; monitoring; data modeling; policy development; DBMS evaluation; server administration; and database lifecycle activities. The role requires an active TS/SCI clearance with polygraph and five years of comparable DBA experience.

Designs, develops, tests, deploys, monitors, and continuously improves machine learning models for complex business and national security missions. Integrates data pipelines, evaluates model performance, ensures data and output quality, and transforms prototypes into scalable production solutions. Requires strong expertise in machine learning algorithms, software architecture, data engineering, model validation, and system integration. The role may lead distributed teams and requires an active TS/SCI clearance with polygraph.

Leads enterprise AI/ML strategy, architecture, development, deployment, and productization for mission-critical initiatives. Builds and mentors engineering teams, advises customers, develops scalable machine learning solutions, and transforms prototypes into secure production systems. Oversees cloud-native architectures, MLOps, CI/CD pipelines, enterprise integration, and model lifecycle management. Supports NLP, predictive analytics, anomaly detection, computer vision, and generative AI while engaging customer and technical leadership.

Performs security assessments and engineering for AI/ML systems, large-scale compute clusters, AWS Cloud infrastructure, networks, and enclave environments. Designs and integrates information assurance architectures, identifies and mitigates security risks, validates security requirements, supports certification and accreditation, and enforces trusted relationships and government security policies. Collaborates with engineering teams and government customers on secure system development and operational deployment.

Designs and leads user experience solutions for AI/ML and cyber intelligence systems. Responsibilities include user research, requirements gathering, interaction design, visual design, storyboards, prototypes, interface guidelines, customer presentations, and collaboration with product owners, developers, stakeholders, and engineering teams. The role supports agile product development in AWS cloud environments and requires an active TS/SCI clearance with polygraph.

Develop and sustain cloud software supporting cyber intelligence and AI/ML capabilities on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java software development, cloud integration, testing, troubleshooting, RESTful services, distributed systems, big-data technologies, Linux development, and technical documentation. The role also involves LLM, RAG, agentic AI, Kubernetes, infrastructure-as-code, CI/CD, and cloud security practices. An active TS/SCI clearance with polygraph is required.

Administers, monitors, troubleshoots, and maintains large-scale Hadoop and AWS cloud clusters supporting AI/ML and national security missions. Responsibilities include Linux systems administration, scripting, distributed storage troubleshooting, network provisioning, configuration management, hardware diagnostics, security compliance, and cloud infrastructure development. The role requires expertise with AWS, Linux, Puppet, Salt, Kubernetes, Docker, distributed databases, provisioning systems, and remote troubleshooting utilities, along with an active TS/SCI clearance with polygraph.

Develops and leads systems engineering activities for cyber intelligence and AI/ML capabilities hosted on large-scale compute clusters and AWS Cloud. Responsibilities include requirements analysis, system architecture and design, interface definition, technical documentation, risk and configuration management, systems integration and testing, verification planning, and security and accreditation support. The role provides technical leadership across integrated product teams and coordinates with government stakeholders to ensure system technical integrity.

Design, develop, test, deploy, and operationalize AI/ML algorithms for mission and business requirements. Build scalable production models, integrate data pipelines, evaluate model performance, and manage training, retraining, monitoring, and continuous improvement. Apply statistical analysis, data governance, software architecture, and data modeling principles. Support system integration and verification/validation activities, with potential leadership of distributed teams and technical customer engagement.

Develop and integrate cloud software supporting cyber intelligence and AI/ML capabilities on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, RESTful services, distributed systems, cloud deployment, DevOps, container orchestration, testing, integration, Linux scripting, and troubleshooting. The role also involves big-data technologies, Hadoop ecosystems, LLMs, RAG, analytics, and secure software engineering for national security missions.

Designs, develops, tests, deploys, monitors, and continuously improves machine learning models supporting business and national security mission requirements. Integrates data pipelines, evaluates model performance, ensures data integrity, and transforms prototypes into scalable production systems. Requires expertise in machine learning frameworks, data engineering, software architecture, statistical analysis, and model validation. The role may provide technical leadership for distributed teams and requires an active TS/SCI clearance with polygraph.

Provides system administration for UNIX, Linux, Solaris, and Windows environments supporting cyber intelligence and AI/ML capabilities. Maintains client/server, storage, network, and mobile systems; performs monitoring, troubleshooting, capacity planning, performance tuning, configuration, and Tier 1 and Tier 2 support. Requires active TS/SCI clearance with polygraph, five years of system administration experience, technical education or equivalent experience, Security+ certification, scripting skills, networking knowledge, and Oracle administration experience.

Provides Tier 1 and Tier 2 IT support, system monitoring, troubleshooting, configuration, maintenance, and user assistance for UNIX, Windows, network, storage, and client/server environments. Manages daily system operations, resolves hardware and software issues, maintains system integrity, and supports cyber and AI/ML capabilities hosted on compute clusters and AWS infrastructure. An active TS/SCI clearance with polygraph and Security+ certification are required.

Develops system requirements, architectures, designs, technical documentation, and integration and test plans for cyber and AI/ML capabilities. Leads systems engineering activities across requirements allocation, interfaces, configuration control, verification, and system implementation. Supports large-scale compute clusters and AWS Cloud infrastructure while coordinating with government stakeholders and cross-functional teams. Requires active TS/SCI clearance with polygraph and seven years of comparable systems engineering experience.

Administer, monitor, troubleshoot, and maintain large Hadoop clusters and AWS cloud infrastructure supporting AI/ML and national security missions. Manage Linux systems, scripting, provisioning, configuration management, distributed storage, hardware diagnostics, security practices, and cloud services. Collaborate across mission-focused teams, lead complex technical tasks, train junior staff, and support technologies including Kubernetes, Docker, load balancers, and observability platforms.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Design, develop, and validate functionally safe software for robotic perception systems. Build safety-critical architecture across Linux and real-time operating systems, create testing and validation frameworks for edge cases, collaborate with machine learning, hardware, and core software teams, and mentor junior engineers on safety-critical coding practices.

Drive MSSP partner growth across AMER by recruiting, onboarding, activating, and expanding strategic managed security service provider relationships. Develop territory recruitment plans, executive partnerships, joint business plans, and indirect routes to market. Help partners launch managed security services, generate pipeline, increase revenue, and accelerate time-to-revenue. Collaborate with sales, channel, marketing, services, and technical teams while managing forecasts, opportunities, executive reviews, and revenue objectives.

Develop and deploy mineral exploration instruments, sensor systems, data acquisition methods, and proprietary software. Integrate geospatial, geophysical, geochemical, geological, and geographic data; build statistically rigorous and physics-based models; identify ore-forming anomalies; and generate 2D and 3D exploration predictions. Collaborate with data scientists, engineers, geoscientists, vendors, and external partners to design field programs, deploy sensors, reduce uncertainty, and guide exploration decisions.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

Lead AI-driven localization product initiatives from concept through production. Build strategic roadmaps, incubate machine-learning capabilities, partner with researchers and engineers, and deliver scalable tools for creators and content operations. Translate user needs into impactful products, communicate strategy to executives and nontechnical stakeholders, and use data, experimentation, and ML evaluation to prioritize work and measure outcomes.

Architect and operate North’s AWS and multi-cloud infrastructure, establishing IaC, CI/CD, security, observability, and disaster-recovery standards. Build AIOps capabilities including anomaly detection, predictive scaling, self-healing remediation, AI-assisted tooling, and cloud cost optimization. Collaborate with DevOps, SRE, Product Engineering, and InfoSec teams to deliver resilient, compliant, highly scalable platforms.

Owns the end-to-end product strategy and execution for AI-powered systems. Defines requirements, evaluation frameworks, quality standards, and system behavior while balancing quality, latency, cost, reliability, safety, and user experience. Partners closely with ML, backend, and client engineering teams to identify failure modes, improve model performance, prioritize roadmaps, and deliver predictable, useful, trusted AI experiences.

Own the end-to-end product direction and quality of an AI email application. Define AI and system requirements, translate model capabilities into product decisions, balance quality, cost, latency, reliability, safety, and user experience, and partner with ML, backend, and client engineers. Establish evaluation frameworks, quality standards, feedback loops, and failure recovery strategies while driving prioritization, execution, experimentation, and user trust in a zero-to-one environment.

Own the end-to-end product direction and quality of an AI-powered email application. Define AI and system requirements, evaluation frameworks, quality standards, and measurable outcomes. Partner closely with ML, backend, and client engineering teams to make trade-offs across quality, latency, cost, reliability, safety, and user experience. Drive prioritization, specifications, experimentation, failure-mode mitigation, and continuous iteration in a technical zero-to-one environment.