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Deep Learning Engineer Jobs in Washington, DC (NOW HIRING)

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Deep Learning Engineer information

See Washington, DC salary details

$43K

$131.2K

$216.8K

How much do deep learning engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for deep learning engineer in Washington, DC is $131,179.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $171,500.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Engineer or AI research director, often involving advanced skills in machine learning frameworks, data modeling, and large-scale system development. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in cutting-edge AI research environments.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What engineers make $500,000?

Senior engineers in high-demand fields such as software, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and data architects at large tech companies or startups often reach this compensation level through base salary, bonuses, and stock options.

What do deep learning engineers do?

Deep learning engineers develop and implement neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. They work with large datasets, use frameworks like TensorFlow or PyTorch, and often require knowledge of programming, mathematics, and machine learning principles.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What engineers make $300,000 a year?

Senior deep learning engineers and AI specialists with extensive experience, advanced skills in machine learning frameworks, and strong domain knowledge can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and work in high-demand industries such as technology, finance, or healthcare, typically involving leadership responsibilities and complex project management.
What are the most commonly searched types of Deep Learning Engineer jobs in Washington, DC? The most popular types of Deep Learning Engineer jobs in Washington, DC are:
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What job categories do people searching Deep Learning Engineer jobs in Washington, DC look for? The top searched job categories for Deep Learning Engineer jobs in Washington, DC are:
Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Washington, DC as of July 2026, with employment types broken down into 72% Full Time, 26% Part Time, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $131,179 per year, or $63.1 per hour.
Machine Learning Engineer with SageMaker Experience

Machine Learning Engineer with SageMaker Experience

Maxiom Technology

Ashburn, VA • On-site, Remote

Full-time

Posted 15 days ago

Job description

Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? Do you thrive in a dynamic and innovative environment, eager to push the boundaries of AI capabilities? If so, we invite you to join our team as we revolutionize the world of AI-driven applications.

Position: Machine Learning Engineer
Location: Remote

Preferred Resource Location: LATAM

About Us:
Maxiom Technology is a cutting-edge technology company at the forefront of AI-driven solutions. We specialize in developing intelligent applications that leverage the power of machine learning and natural language processing. Our team consists of talented individuals who are dedicated to creating groundbreaking solutions that transform industries.

Responsibilities:

- Collaborate with cross-functional teams to design, develop, and deploy machine learning models using Amazon SageMaker.
- Utilize your expertise in prompt engineering to craft effective inputs for LLM models to achieve desired outputs.
- Fine-tune and optimize LLM models to enhance performance, efficiency, and accuracy.
- Design and implement experiments to evaluate model performance, iteratively improving results.
- Stay up-to-date with the latest advancements in machine learning, particularly in the realm of LLM models and prompt engineering techniques.
- Identify and troubleshoot issues related to model performance, data quality, and integration.
- Contribute to the entire machine learning lifecycle, from data preprocessing and training to deployment and monitoring.
- Collaborate with software engineers to integrate machine learning solutions into our applications.
- Document your work, best practices, and findings to share knowledge across the team.

Qualifications:

- Bachelor's degree in Computer Science, Engineering, or a related field (Master's or PhD preferred).
- Proven experience in developing and deploying machine learning models using Amazon SageMaker.
- Strong background in prompt engineering techniques for fine-tuning LLM models.
- Proficiency in programming languages such as Python for model development and experimentation.
- Solid understanding of natural language processing concepts and techniques.
- Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and their integration with SageMaker.
- Experience with data preprocessing, feature engineering, and data augmentation.
- Problem-solving skills to diagnose and address model performance and data-related issues.
- Excellent communication skills to collaborate effectively within multidisciplinary teams.
- Ability to adapt to evolving technologies and learn quickly in a fast-paced environment.

Bonus Skills:

- Publications or contributions to the machine learning community.
- Experience with cloud services (AWS, Azure, Google Cloud) and containerization technologies.
- Knowledge of DevOps practices for model deployment and monitoring.

Why Join Us:

- Opportunity to work on cutting-edge projects that push the boundaries of AI technology.
- Collaborative and inclusive work environment that values innovation and creativity.
- Access to resources and support for continuous learning and professional growth.
- Competitive compensation package and benefits.

If you are an ambitious Machine Learning Engineer with a proven track record in SageMaker, prompt engineering, and LLM model tuning, we would love to hear from you. Join us in our mission to create groundbreaking AI solutions that shape the future. Apply now by sending your resume and a cover letter.

Maxiom Technology is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.