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Deep Learning Ai Jobs in Washington (NOW HIRING)

Senior Data Scientist

Washington, DC · On-site

$130 - $150/hr

Conceptualize, plan, design, and develop deep learning/AI algorithms for multi-objective optimization focused on ERO resource allocation, logistics, and enforcement prioritization. * Lead MLOps ...

AI Research Scientist

Washington, DC · On-site

$120 - $180/hr

Conduct original research in areas such as machine learning, deep learning, natural language processing, computer vision, or reinforcement learning. Design, implement, and evaluate novel AI ...

Python, Machine Learning, Deep Learning, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, SQL, NLP, Computer Vision, Generative AI, LLM, Prompt Engineering, RAG, Vector Databases, REST APIs ...

AI/ML Engineer With DevOps

Ashburn, VA · On-site

$54 - $74/hr

Adtech seeks a motivated, career and customer-oriented AI/ML Engineer . This is currently a hybrid ... Experience in using deep learning frameworks (PyTorch, TensorFlow, Keras) and computer vision ...

Showing results 41-60

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 are popular job titles related to Deep Learning Ai jobs in Washington?

For Deep Learning Ai jobs in Washington, the most frequently searched job titles are:

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

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

Infographic showing various Deep Learning Ai job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Senior Applied Machine Learning Scientist

The Washington Post

Washington, DC

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


Job description

Join the future of news

We're on a mission to deliver riveting storytelling for all of America. At The Washington Post, you'll help reinvent news. Our work is driven by a deep investigative spirit and enhanced by innovation to bring audiences closer to the stories that matter most.

About Our Team

The Washington Post is powered by the passion and talent of our people. It takes all of us to reinvent news. Beyond our award-winning Newsroom and Opinions teams, we work across many departments, including Brand & Events, Communications, Customer Care, Engineering & Product, Finance, Human Resources, Legal, Marketing & Advertising, Print Operations, and Sales.

Why This Role Matters

The Washington Post is looking for a Senior Applied Machine Learning Scientist to lead the development of advanced AI/ML systems that power the next generation of journalism. This role will focus on Ask The Post, AI-powered search, retrieval, ranking, content understanding, and generative AI-powered reader experiences.
You will work at the intersection of generative AI, information retrieval, NLP, ranking, recommender systems, and experimentation to build intelligent systems that serve The Post's journalism, readers, and business goals.

What Motivates You
  • You value world-class journalism and want to build technology that strengthens that mission.

  • You enjoy solving ambiguous, high-impact problems with practical AI/ML solutions.

  • You are excited by advances in generative AI, search, retrieval, ranking, and recommendation.

  • You communicate clearly, collaborate well, and thrive in a feedback-driven environment.

  • You are eager to learn, share, and apply the latest AI/ML techniques.

How You'll Support the Mission
  • Lead applied research and development for AI/ML systems across generative AI, search, retrieval, ranking, content understanding, and recommendation.

  • Formulate ambiguous product and business challenges as scientific problems with clear metrics, experiments, and success criteria.

  • Design, train, evaluate, and deploy advanced AI/ML models, including fine-tuned mid-range LLMs, dense and sparse embedding systems, VLMs, learning-to-rank models, agentic workflows, and efficient model-serving approaches for conversational search systems.

  • Build and improve AI-powered experiences such as Ask The Post, semantic search, content understanding, question answering, ranking, and intelligent discovery.

  • Design rigorous offline and online evaluations, including relevance evaluation, ranking metrics, retrieval quality, A/B testing, and causal analysis.

  • Develop scalable and efficient production ML systems with attention to latency, reliability, cost, monitoring, and maintainability.

  • Analyze large-scale behavioral, content, search, and interaction data to guide model and product improvements.

  • Collaborate with scientists, engineers, data teams, product managers, editors, and other business stakeholders to deliver impactful AI/ML solutions.

  • Provide technical leadership by shaping roadmaps, mentoring junior scientists and engineers, and promoting scientific rigor.

  • Communicate technical approaches, tradeoffs, results, and business impact to technical and non-technical audiences.

The Skills and Experience You BringQualifications
  • Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related technical field.

  • 4+ years of experience in applied machine learning, AI, data science, information retrieval, NLP, recommender systems, or a related field.

  • Strong experience with Python and at least one ML framework such as PyTorch, TensorFlow, or JAX.

  • Experience designing, evaluating, and deploying ML models using large-scale datasets.

  • Strong foundation in machine learning, statistical analysis, experimental design, and model evaluation.

  • Experience with search, ranking, retrieval, NLP, GenAI, or recommendation systems.

Preferred Qualifications

  • Master's or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Information Retrieval, NLP, or a related field.

  • Deep familiarity with modern ML architectures, including transformer-based models, embedding models, two-tower architectures, LLMs, VLMs, and their applications in large-scale search, retrieval, ranking, and recommender systems.

  • Hands-on experience building production systems for semantic search, retrieval-augmented generation, question answering, ranking, content understanding, recommendation, or GenAI-powered products.

  • Experience with AWS, GCP, Spark, Beam, BigQuery, or similar cloud and big-data technologies.

  • Experience with LLM/VLM evaluation, model calibration, uncertainty estimation, interpretability, responsible AI, or production model optimization.

  • Experience with deep learning, reinforcement learning, multi-armed bandits, causal inference, or learning-to-rank methods.

  • Publications, patents, open-source contributions, or technical talks in AI/ML, NLP, information retrieval, recommender systems, GenAI, or related areas.

  • Experience mentoring scientists or engineers and influencing technical roadmaps.

    Collaboration makes us stronger. That's why our offices are designed with open layouts, modern technology, and easy access to transportation. With certain exceptions for newsgathering and business travel, we work on-site five days a week.Compensation and Benefits

    Wherever you are in your life or career, The Washington Post offers comprehensive and inclusive benefits for every step of your journey:

    • Competitive medical, dental and vision coverage

    • Company-paid pension and 401(k) match

    • Three weeks of vacation and up to three weeks of paid sick leave

    • Nine paid holidays and two personal days

    • 20 weeks paid parental leave for any new parent

    • Robust mental health resources

    • Backup care and caregiver concierge services

    • Gender affirming services

    • Pet insurance

    • Free Post digital subscription

    • Leadership and career development programs

    Benefits may vary based on the job, full-time or part-time schedule, location, and collectively bargained status.

    The salary range for this position is:

    $131,500 - $219,100 Annual

    The actual salary within this range will depend on individual skills, experience, and qualifications as they relate to specific job requirements. This position may be eligible for a bonus or incentive program, and a member of the Talent Acquisition team will discuss bonus payment terms and conditions during the interview process.

    Your story awaits. Apply today!

    Learn more about The Post at careers.washingtonpost.com.