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Computer Science Artificial Intelligence Jobs in Baltimore, MD

... data science, computer science, artificial intelligence, aerospace, systems engineering, or a related technical field * Demonstrated experience developing or leading advanced analytics, AI/ML ...

Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Computer Engineering, Mathematics, Statistics, or related field. * 5+ years of related professional ...

Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Computer Engineering, Mathematics, Statistics, or related field. * 5+ years of related professional ...

Emphasizes theoretical foundations alongside practical implementation and connects computer science to artificial intelligence, distributed systems, and industry engineering practices. * Curriculum ...

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Computer Science Artificial Intelligence information

See Baltimore, MD salary details

$50.2K

$110.6K

$136.6K

How much do computer science artificial intelligence jobs pay per year?

As of Aug 15, 2026, the average yearly pay for computer science artificial intelligence in Baltimore, MD is $110,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,900.00 and $136,100.00 per year, depending on experience, location, and employer.

Can I get an artificial intelligence job with a computer science degree?

A computer science degree provides a strong foundation for artificial intelligence (AI) roles, which often require knowledge of programming languages like Python, machine learning algorithms, and data analysis. Many AI jobs also value practical experience, internships, and familiarity with tools such as TensorFlow or PyTorch.

What computer science artificial intelligence jobs are in high demand?

High-demand artificial intelligence jobs in computer science include AI engineer, machine learning engineer, data scientist, and research scientist. These roles often require skills in programming languages like Python, knowledge of deep learning frameworks, and experience with large datasets, with industries such as tech, finance, healthcare, and autonomous vehicles actively hiring for these positions.

What does a typical day look like for someone working in computer science artificial intelligence?

A typical day in a Computer Science Artificial Intelligence role often involves researching and developing new models, collaborating with data scientists and software engineers, and testing or optimizing machine learning algorithms. You may spend a significant amount of time analyzing datasets, building prototypes, and reviewing code, as well as meeting with multidisciplinary teams to align on project goals. The role is dynamic, with a mixture of individual problem-solving and group brainstorming to tackle complex challenges. This variety ensures continual learning and hands-on interaction with the latest technological advancements in artificial intelligence.

What are the key skills and qualifications needed to thrive in computer science artificial intelligence, and why are they important?

To thrive in a Computer Science Artificial Intelligence role, you need strong programming skills (Python, Java, or C++), a solid understanding of machine learning algorithms, and typically at least a bachelor's degree in computer science or related fields. Hands-on experience with frameworks and tools like TensorFlow, PyTorch, Scikit-learn, and familiarity with cloud platforms is highly desirable, and certifications such as AWS Certified Machine Learning can be advantageous. Analytical thinking, problem-solving, teamwork, and effective communication are important soft skills for success in both independent and collaborative settings. These skills and qualifications enable professionals to design, implement, and deploy AI solutions that address real-world business challenges.

What is a computer science artificial intelligence?

A Computer Science Artificial Intelligence (AI) job involves developing, implementing, and improving AI technologies using machine learning, deep learning, and data analysis techniques. Professionals in this field work on algorithms, automation, and intelligent systems that can solve complex problems across industries like healthcare, finance, and robotics. Roles may include AI engineer, data scientist, or machine learning specialist, requiring strong programming skills in languages like Python and knowledge of AI frameworks.

What are the most commonly searched types of Computer Science Artificial Intelligence jobs in Baltimore, MD?

The most popular types of Computer Science Artificial Intelligence jobs in Baltimore, MD are:

What are popular job titles related to Computer Science Artificial Intelligence jobs in Baltimore, MD?

For Computer Science Artificial Intelligence jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Computer Science Artificial Intelligence jobs in Baltimore, MD look for?

The top searched job categories for Computer Science Artificial Intelligence jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Computer Science Artificial Intelligence jobs?

Cities near Baltimore, MD with the most Computer Science Artificial Intelligence job openings:

Infographic showing various Computer Science Artificial Intelligence job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $110,630 per year, or $53.2 per hour.

AI/ML Decision Intelligence Lead

Peraton

Bowie, MD • On-site

Full-time

Re-posted yesterday


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

51st of 224 rated it services


Job description

Responsibilities

Responsibilities

Peraton Labs is seeking an AI/ML Decision Intelligence Lead to support the BNATCS CTO organization in developing advanced analytics, AI-enabled decision support, and agentic AI capabilities for one of the nation's most significant aviation modernization efforts.

The BNATCS CTO is building the analytical, data, and AI foundation needed to help program and government stakeholders understand complex program dynamics, identify emerging risks, evaluate tradeoffs, and make better-informed decisions across a large-scale aviation system-of-systems environment. This includes integrating and analyzing programmatic, engineering, operational, and workstream data; developing decision-grade analytical products and shaping how advanced AI and analytics are applied to support execution, modernization, and mission outcomes.

This role will serve as a senior technical leader responsible for designing, developing, and guiding advanced analytics and AI capabilities that turn complex data into actionable insight. Candidates for this role should have deep hands-on technical depth, strong analytical judgment, comfort working across ambiguous data environments, and the ability to brief senior stakeholders with clarity, confidence, and credibility.

The ideal candidate for this position is a technical leader who can bridge artificial intelligence, machine learning, operations research, statistical modeling, systems thinking, and mission-focused execution by helping define analytical approaches, lead complex technical development efforts, guide data fusion strategies, mentor technical contributors, and shape the BNATCS CTO roadmap for AI-enabled decision intelligence and agentic analytics.

Key responsibilities may include, but are not limited to:

  • Lead the design, development, and application of AI/ML, advanced analytics, and decision intelligence capabilities supporting BNATCS CTO priorities
  • Transform complex programmatic, engineering, operational, and aviation-domain data into actionable insight for leadership, technical teams, and government stakeholders
  • Develop analytical frameworks that support continuous monitoring, evaluation, and improvement of program performance, technical progress, operational readiness, and emerging risk areas
  • Design and guide predictive models that identify early indicators of risk across schedule, cost, technical integration, operational performance, data readiness, and mission execution
  • Apply machine learning, statistical modeling, operations research, simulation, optimization, and probabilistic methods to support scenario analysis, tradeoff evaluation, resource planning, and decision support
  • Lead data fusion strategies across heterogenous data sources, including multi-source correlation, entity resolution, temporal alignment, data quality evaluation, lineage, and analytical readiness
  • Identify, assess, and align data sources required to support advanced analytics, agentic AI workflows, visualization products, and decision-support capabilities
  • Develop strategies for working with sensitive, incomplete, inconsistent, or restricted data, including potential use of synthetic data generation, privacy-preserving methods, and representative test datasets
  • Evaluate opportunities to apply agentic AI, transformer-based methods, natural language processing, retrieval augmented generation, knowledge graphs, or other emerging AI techniques to mission relevant analytical workflows
  • Ensure analytical methods are interpretable, reliable, testable, reproducible, and appropriate for high-governance, safety-conscious, and mission-critical environments
  • Define evaluation approaches for AI/ML and analytical products, including performance measures, confidence communication, assumptions, limitations, validation methods, and operational suitability
  • Partner with data, architecture, engineering, visualization, and workstream stakeholders to translate operational needs into measurable analytical outputs and technical delivery plans
  • Create executive-ready briefings, analytical products, technical roadmaps, decision-support artifacts, and recommendations that communicate complex findings clearly to senior stakeholders
  • Brief FAA, BNATCS, and internal leadership on analytical products, model results, decision implications, technical risks, capability gaps, and recommended paths forward
  • Establish best practices for decision intelligence, model governance, reproducible analysis, documentation, data-driven program insight, and responsible AI use within the BNATCS environment
  • Identify analytical risks early, including data quality concerns, weak assumptions, model drift, insufficient validation, governance gaps, or operational adoption barriers, and recommend mitigation strategies
Qualifications

Required Qualifications

  • 12+ years of experience with a BS/BA, 10+ years with a MS/MA, or 6+ years with a PhD in AI/ML, data science, computer science, artificial intelligence, aerospace, systems engineering, or a related technical field
  • Demonstrated experience developing or leading advanced analytics, AI/ML, predictive modeling, simulation, optimization, or decision-support capabilities in complex technical environments
  • Strong ability to transform large, complex, or ambiguous datasets into decision-ready insights for senior technical, operational, programmatic, or government stakeholders
  • Experience framing complex analytical problems, selecting appropriate methods, developing evaluation approaches, and communicating assumptions, limitations, confidence, and decision implications
  • Experience with multi-source data integration, data fusion, data quality, assessment, temporal alignment, entity resolution, or analytical preparation of heterogenous datasets
  • Experience applying machine learning or modern AI methods to real-world problems, with the judgment to balance model performance, interpretability, reliability, governance, and operational usefulness
  • Experience supporting mission-critical, safety-conscious, highly regulated, government, aviation, defense, transportation, infrastructure, or large-scale systems environments
  • Demonstrated ability to lead technical contributors, mentor analytical staff, review technical work, and guide multidisciplinary execution across AI/ML, analytics, data, and engineering teams
  • Familiarity with agentic AI, intelligent workflow automation, human-machine teaming, decision intelligence, or AI-enabled operational support systems
  • Experience with transformer-based models, natural language processing, retrieval augmented generation, knowledge graphs, GraphRAG, or semantic data integration
  • Strong executive communication skills, including the ability to brief senior leaders on complex analytical, technical, and strategic topics
  • Ability to work effectively with government stakeholders, technical teams, program leaders, and cross-functional partners in fast-moving and ambiguous environments
  • US Citizenship with the ability to obtain/maintain an FAA Public Trust

Desired Qualifications

  • Experience with FAA, aviation, air traffic, airline operations, transportation systems, National Airspace System modernization, or other complex system-of-systems domains
  • Familiarity with MLOps, model monitoring, evaluation automation, reproducible pipelines, data lineage, model governance, and analytical lifestyle management
  • Experience creating executive dashboards, analytical decision-support tools, operational insight products, or visualization strategies for senior decision makers
  • Experience establishing analytical standards, governance practices, model evaluation frameworks, or responsible AI practices in high-governance environments

Peraton Labs is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. We are committed to creating a diverse and inclusive workplace where all team members feel valued and can contribute their best work.

Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.

Target Salary Range$146,000 - $234,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.EEOEEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.Employment Type: FULL_TIME

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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017