Top Senior Machine Learning Jobs in Baltimore, MD

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

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

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Principle Solutions Architect will lead the solutioning process for business development, manage proposal efforts, and mentor team members, focusing on federal government contracts.

Lead capture solutioning for large federal pursuits by architecting technical solutions, guiding capture and proposal teams, defining system designs and interfaces, and contributing to proposal volumes. Works with clients to assess requirements and translate solutions across cloud, data, cyber, AI/ML, RPA, and software development approaches.

Lead analytic approaches to extract meaning from large, messy NSA/CSS datasets. Design and implement ML and statistical models, manage/curate data, translate mission needs into technical requirements, and communicate results to non-technical stakeholders.

The Senior Cloud Architect will provide technical expertise to sustain critical mission-related software and systems for a U.S. Government customer, focusing on cloud-based hybrid computing design and architecture.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Analyze SIGINT and cybersecurity data, develop exploitation plans, collaborate with teams, and apply analytical techniques to distill insights from data.

As a Target Digital Network Analyst, you will analyze data, ensure target continuity, maintain databases, identify intelligence gaps, and collaborate with teams.

The VP will transform R&D operations by embedding AI into product workflows, enhancing efficiency and decision-making across teams. They will lead system redesign, implement AI-driven analytics, and establish KPIs for continuous improvement.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

Lead product strategy for AI-driven security operations, defining the vision and roadmap for agentic workflows, collaborating with teams, and measuring success metrics.

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.

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 Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

Own and close enterprise customer deals, develop expansion opportunities, educate customers on AI architectures, engage with multiple stakeholders, and collaborate with product and engineering teams.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the development of a new product area focused on improving onsite customer experiences using AI and machine learning to optimize marketing conversions. Oversee product strategy, measure performance, and collaborate with teams to ensure successful product launches.

As a Staff ML Research Engineer, you will develop and optimize ML algorithms for drug discovery, transitioning high-impact prototypes into robust products and managing software development across the lifecycle.

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 Engineering Manager will lead a multidisciplinary team focusing on machine learning solutions for fraud detection, ensuring system accuracy and performance while driving innovation and collaboration across departments.