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Deep Learning Developer Jobs in Seattle, WA (NOW HIRING)

Microsoft

Research Intern - Deep Learning Group

Redmond, WA · On-site

$8K - $14K/mo

... and engineers, who pursue innovation in a range of scientific and technical disciplines to help ... The Deep Learning group at the Microsoft Research Redmond lab is seeking applicants for 2026 summer ...

Adobe

Machine Learning Engineer

Seattle, WA · On-site

$93K - $125K/yr

Develop, evaluate, and deploy ML models using classical, deep learning, and GenAI approaches ... Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Deep knowledge of math, probability, statistics, and algorithms * Ability to write robust code in Python, Java, and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Deep knowledge of math, probability, statistics, and algorithms * Ability to write robust code in Python, Java, and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and ...

Adobe

Sr. Machine Learning Engineer 4

Seattle, WA · On-site

$118K - $163K/yr

Develop, evaluate, and deploy ML models using classical, deep learning, and GenAI approaches ... Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required ...

Cisco

Principal Machine Learning Engineer

Bellevue, WA · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Preferred : • Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale ...

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Deep Learning Developer information

See Seattle, WA salary details

$20

$43

$57

How much do deep learning developer jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for deep learning developer in Seattle, WA is $43.75, according to ZipRecruiter salary data. Most workers in this role earn between $37.21 and $48.70 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other resilient roles include AI ethicists, who address ethical considerations, and AI system trainers, who curate and annotate data to improve AI performance. These jobs involve complex problem-solving and human oversight that are less easily automated.

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

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Seattle, WA as of May 2026, with employment types broken down into 1% Locum Tenens, 31% Full Time, 62% Part Time, 5% Contract, and 1% Nights. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $90,993 per year, or $43.7 per hour.
Senior Deep Learning Tools Engineer - CUDA Tile

Senior Deep Learning Tools Engineer - CUDA Tile

NVIDIA

Seattle, WA • On-site

$118K - $163K/yr

Full-time

Posted 28 days ago

Job description

Job Summary:
NVIDIA is building advanced compiler technologies to accelerate AI workloads, and they are looking for an engineer focused on performance validation, analysis, and tracking. In this role, you will work at the intersection of deep learning compilers, GPU systems, and automation infrastructure, ensuring that performance improvements are measurable, scalable, and continuously validated over time.
Responsibilities:
• Design and develop performance testing frameworks for deep learning compilers and workloads
• Build and maintain automated pipelines (CI/CD) to continuously track performance across models, hardware, and compiler changes
• Implement benchmarking systems to measure latency, throughput, and efficiency of AI and HPC workloads
• Analyze performance trends over time and identify regressions, bottlenecks, and optimization opportunities
• Partner with compiler and architecture teams to debug and resolve performance issues
• Develop tools and dashboards for performance visualization, reporting, and insights
• Enable scalable testing across diverse GPU systems and environments
• Improve infrastructure to ensure reliable, reproducible, and high-signal performance data
Qualifications:
Required:
• BS, MS, or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field
• 5+ years of software engineering experience, including experience in performance engineering, benchmarking, or systems optimization
• Strong programming skills in Python (C++ is a plus)
• Experience with CI/CD systems and automation frameworks
• Familiarity with hardware-aware performance analysis (GPUs, accelerators, or similar systems)
• Experience working with deep learning frameworks such as PyTorch, TensorFlow, JAX, or TensorRT
• Background in data analysis, profiling, and regression tracking
• Ability to debug complex system-level issues across software and hardware layers
Preferred:
• Experience with GPU performance analysis and optimization
• Understanding of compiler internals (LLVM, MLIR, CUDA compilation flow)
• Experience building performance dashboards and large-scale telemetry systems
• Familiarity with hardware/software co-design or low-level performance tuning
• Experience with distributed testing infrastructure or large-scale benchmarking systems
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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