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Multimodal Learning Jobs in Virginia (NOW HIRING)

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and ...

Experience analyzing large, multimodal datasets from a variety of sensors * Proficiency in ... Experience in artificial intelligence, machine learning, and data analytics * Experience ...

Showing results 41-60

Multimodal Learning information

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are the key skills and qualifications needed to thrive in multimodal learning, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

What are some common challenges faced by professionals working in multimodal learning roles, and how can they be addressed?

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.
What job categories do people searching Multimodal Learning jobs in Virginia look for? The top searched job categories for Multimodal Learning jobs in Virginia are:
What cities in Virginia are hiring for Multimodal Learning jobs? Cities in Virginia with the most Multimodal Learning job openings:
Infographic showing various Multimodal Learning job openings in Virginia as of August 2026, with employment types broken down into 67% Full Time, and 33% Temporary. Highlights an 100% In-person job distribution.

Transportation Data Scientist (AI Solutions)

Leidos

Falls Church, VA • On-site

$100K - $120K/yr

Full-time

Medical, Retirement, PTO

Re-posted 15 days ago


Leidos rating

8.3

Company rating: 8.3 out of 10

Based on 151 frontline employees who took The Breakroom Quiz

77th of 485 rated business services


Job description

Description

Are you interested in improving and shaping the transportation industry in a group of intelligent and motivated individuals?  Leidos operates the Federal Highway Administration’s (FHWA) Saxton Transportation Operations Laboratory (STOL), a USDOT research lab focused on the improvement of transportation operations, safety, mobility, and environmental impacts.  STOL provides a variety of services to support the advancement and deployment of emerging technologies, including vehicle automation and communication. 

Leidos is seeking a talented Transportation Data Scientist at the junior to mid-level to support FHWA-funded projects at the intersection of AI, data science, and transportation. This role will involve assisting in the development and deployment of AI/ML models for applications such as vehicle load classification using weigh-in-motion (WIM) data and imagery, crash prediction in traffic management centers (TMCs), and creating data ecosystems for trustworthy AI. The ideal candidate will have foundational experience in AI model development, data integration, and stakeholder engagement, with a passion for exploring opportunities to apply AI in state-level transportation initiatives. This position offers the chance to contribute to innovation in a dynamic, federally supported research environment.

Location: This role will be expected to work full-time at the customer site in McLean, VA

Candidate MUST:

Be currently located in the United States for the current three consecutive years and be eligible for a Public Trust Clearance.

https://careers.leidos.com/search/jobs?q=stol&ns_job_category=stol-jobs

Primary Responsibilities

•           Assist in conducting data and literature reviews, including targeted searches for AI methods, datasets, and technologies relevant to freight analytics, traffic safety, and operations (e.g., sensor fusion, computer vision, and multimodal AI).

•           Prepare and integrate datasets for AI use cases, including cleaning, normalizing, enriching, and fusing multi-source data (e.g., traffic logs, imagery, weather, and permitting records) while addressing quality issues like inconsistency, sparsity, and bias.

•           Contribute to the design, development, and deployment of AI/ML models for transportation applications.

•           Evaluate AI model performance under diverse conditions, such as varying data quality levels, and provide recommendations for improving model robustness, scalability, and trustworthiness in real-world transportation environments.

•           Support stakeholder outreach and engagement, including organizing peer exchanges, workshops, and technical briefings with state DOTs, MPOs, enforcement agencies, and vendors to gather insights on AI applications.

•           Collaborate with cross-functional teams to ensure project alignment with USDOT goals, including risk management, quality assurance, and compliance with federal standards.

•           Contribute to monthly progress reporting, risk mitigation, and iterative model refinement based on federal feedback.

Required Qualifications

  • Master’s degree in computer science, Data Science, Artificial Intelligence, Transportation Engineering, or a related field; Ph.D. preferred.
  • 2+ years of professional experience (NON-academic) in data science and AI/ML, with demonstrated familiarity in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), data processing tools (e.g., Pandas, NumPy), and AI techniques (e.g., deep learning, generative AI like GANs, computer vision, LLMs).
  • Must have HANDS-ON experience in AI Solution Development.
  • Strong experience in data preparation and integration, including ETL processes, handling multimodal data (e.g., imagery, sensor data, time-series), and addressing data quality challenges in real-world applications.
  • Strong analytical skills with familiarity in model evaluation metrics (e.g., AUC, accuracy, scalability) and testing AI systems under varied conditions.
  • Excellent communication and collaboration skills, with experience in stakeholder engagement, technical reporting, and presenting complex AI concepts to non-technical audiences.
  • Ability to work in a fast-paced, research-oriented environment with travel up to 20% for stakeholder meetings, site visits, or conference support.
  • Ability to obtain and maintain a Public Trust clearance (which includes three years of immediate residency in the US).
  • All applicants must be legally authorized to work in the United States.

Preferred Qualifications

  • Prior experience working with state DOTs or federal transportation agencies (e.g., FHWA, USDOT) on AI initiatives, including prototyping and developing AI application in ITS.
  • Familiarity with transportation-specific data sources (e.g., HSIS, SHRP2, NGSIM) and standards (e.g., SAE J2735 for V2X).
  • Experience in synthetic data generation, generative AI (e.g., LLMs), or physics-informed ML for transportation applications.
  • Knowledge of federal AI governance, risk management, and equity considerations in transportation.
  • Project management experience, including leading AI tasks in multi-agency initiatives or contributing to communities of practice (CoPs).
  • Publications or presentations in AI/transportation conferences (e.g., TRB, ITS America).

Anticipated salary range for this role is $100,000-$120,000

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:June 26, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:Pay Range $87,100.00 - $157,450.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits.

Securing Your Data

Beware of fake employment opportunities using Leidos’ name. Leidos will never ask you to provide payment-related information during any part of the employment application process (i.e., ask you for money), nor will Leidos ever advance money as part of the hiring process (i.e., send you a check or money order before doing any work). Further, Leidos will only communicate with you through emails that are generated by the Leidos.com automated system – never from free commercial services (e.g., Gmail, Yahoo, Hotmail) or via WhatsApp, Telegram, etc. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.

If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.


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About Leidos

Sourced by ZipRecruiter

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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