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Multimodal Learning Jobs in Virginia (NOW HIRING)

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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.

Cyber Digital Trust & Online Safety Manager

Deloitte

Richmond, VA • On-site

Full-time

Posted 20 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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