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Deep Learning Ai Jobs in Virginia (NOW HIRING)

Senior AI/ML Engineer

Alexandria, VA ยท On-site

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI / ML models, including NLP, LLM-based pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize ...

AI/ML Engineer, Senior

Springfield, VA ยท Hybrid

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLMbased pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize scalable ...

AI/ML Engineer, Senior

Alexandria, VA ยท On-site

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLM-based pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize ...

AI/ML Engineer, Senior

Alexandria, VA ยท On-site

$99 - $225/hr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLMbased pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize scalable ...

New

AI/ML Engineer, Senior

Springfield, VA ยท On-site

$99 - $225/hr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLMbased pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize scalable ...

New

AI/ML Engineer, Senior

Alexandria, VA ยท Hybrid

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLMbased pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize scalable ...

AI/ML Engineer, Senior

Alexandria, VA ยท On-site

$99K - $225K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Design, develop, and implement AI/ML models, including NLP, LLM-based pipelines, deep learning architectures, and computer vision models, aligned to mission requirements. * Build and optimize ...

... ai, you will: * Play a key role in architecting the algorithms and models that will power our products * Train on a dedicated high-performance compute cluster specialized for deep learning research

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Deep Learning Ai information

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

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

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What cities in Virginia are hiring for Deep Learning Ai jobs?

Cities in Virginia with the most Deep Learning Ai job openings:

Infographic showing various Deep Learning Ai job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Research Scientist - Machine Learning

AIToolboard

Richmond, VA โ€ข On-site

$120 - $190/hr

Other

Posted yesterday

New


Job description

Jobs / AI Research Scientist - Machine Learning

AI Research Scientist - Machine Learning

Full-time

About the Role

Our client is seeking a brilliant and innovative AI Research Scientist specializing in Machine Learning to join their cutting-edge R&D team in Richmond, Virginia, US. This role is at the forefront of developing next-generation AI technologies and algorithms. You will be responsible for designing, implementing, and evaluating advanced machine learning models, conducting groundbreaking research, andcontributing to high-impact AI applications. The ideal candidate possesses a strong academic background, a deep understanding of ML principles, and a passion for pushing the boundaries of artificial intelligence.Key Responsibilities:Conduct advanced research in machine learning, deep learning, and related AI fields. Design, develop, and implement novel algorithms and models for complex AI problems. Experiment with various ML techniques, including supervised, unsupervised, reinforcement learning, and neural networks. Analyze large datasets, preprocess data, and extract meaningful features for model training. Evaluate model performance, identify areas for improvement, and iterate on designs. Collaborate with software engineers to deploy and integrate AI models into production systems. Stay current with the latest advancements in AI and ML research through literature review and conference participation. Publish research findings in leading scientific journals and present at conferences. Mentor junior researchers and interns, fostering a collaborative research environment. Contribute to the intellectual property portfolio through patent applications.Qualifications:Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field. Proven research experience demonstrated through publications in top-tier AI/ML conferences and journals (e.g., NeurIPS, ICML, ICLR, CVPR). Strong theoretical foundation in machine learning, deep learning, and statistical modeling. Proficiency in programming languages such as Python, and experience with ML libraries like TensorFlow, PyTorch, scikit-learn. Experience with data manipulation and analysis tools. Ability to design and conduct rigorous experiments, interpret results, and draw insightful conclusions. Excellent problem-solving skills and creativity in developing novel solutions. Strong communication and presentation skills, with the ability to articulate complex technical concepts. Experience with distributed computing frameworks (e.g., Spark) is a plus. Experience in specific domains like NLP, computer vision, or reinforcement learning is highly desirable. Join a forward-thinking team that is shaping the future of AI. This exciting opportunity is based in Richmond, Virginia, US .

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