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

Machine Learning Engineer

Seattle, WA · On-site

$175 - $308.50/hr

In this position, you will be part of our extraordinary team of Computer Graphics, Computer Vision and Deep Learning researchers and engineers to discover and build solutions to previously-unsolved ...

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

In this position, you will be part of our extraordinary team of Computer Graphics, Computer Vision and Deep Learning researchers and engineers to discover and build solutions to previously-unsolved ...

As a Staff Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our ... Experience with one or more of Deep Learning algorithms, Large Language Models, Causal Inference ...

Showing results 41-60

Deep Learning Developer information

See Seattle, WA salary details

$20

$43

$57

How much do deep learning developer jobs pay per hour?

As of Aug 10, 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?

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 is a deep learning developer?

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.

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.

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.
Infographic showing various Deep Learning Developer job openings in Seattle, WA as of June 2026, with employment types broken down into 1% As Needed, 95% Full Time, 2% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $90,993 per year, or $43.7 per hour.

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND

Apple Inc.

Seattle, WA • On-site

$142.30 - $263.30/hr

Other

Medical, Dental, Retirement

Re-posted 24 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND

Seattle, Washington, United States Machine Learning and AI

The Machine Intelligence, Neural Design (MIND) team, part of Apple’s AIML organization, is leading Apple-wide innovation on HW/SW co-design for efficient inference. With roots in ML, computer vision, and energy efficiency research, our team is strategically positioned to contribute to diverse initiatives ranging from shipping features in well-known Apple products to ambitious, long‑term research projects.

We are seeking a hands‑on Machine Learning Engineer to drive the data & evaluation lifecycle for our production models. In this role, you will focus on designing and scaling high‑performance data processing pipelines, ensuring data quality, performing in-depth failure analysis on production models, and implementing advanced data augmentation techniques to boost model performance. This includes but is not limited to crafting creative techniques to analyze audio & video datasets, designing metrics to understand user behavior & evaluate performance of machine learning models. You will innovate across the entire end‑to‑end ML production pipeline, bridging the gap between hardware, software, and modeling, ensuring our ML systems are robust, efficient, and scalable.

Description

We are seeking a Machine Learning Engineer to design and deliver innovative features and models that advance our ML systems. In this role, you will scale model evaluation workflows, build robust data pipelines, and optimize performance across the stack.

  • Pipeline Scaling & Optimization: Design, build, and maintain scalable ETL/ELT data pipelines using tools like Spark and Airflow to handle large‑scale datasets. Optimize existing pipelines for efficiency, latency, and cost.
  • Data Augmentation & Synthesis: Research and implement advanced data augmentation techniques (e.g., GANs, semantic augmentation, synthetic data generation) to address data scarcity and imbalanced datasets.
  • Data Quality & Monitoring: Implement data observability and automated data validation checks to identify data drift, schema violations, and outliers in real‑time.
  • Failure Analysis & Debugging: Perform root‑cause analysis on production model failures, diagnosing issues between data inputs and model outputs using advanced statistical methods.
  • Model Evaluation: Collaborate with other machine learning engineers to productize models, implementing robust evaluation frameworks, including experimentation and performance monitoring.
Minimum Qualifications
  • Proficiency in working with unstructured data, specifically video & audio signals, for object detection, pattern recognition, feature extraction and segmentation.
  • Proficiency with Python and deep learning frameworks like PyTorch.
  • Expertise in designing metrics, and conducting metric change & performance analysis for model evaluation.
  • Strong problem‑solving skills in analyzing complex, ambiguous problems and clearly presenting sophisticated technical concepts to both expert and non‑expert audiences.
  • Master’s degree or equivalent experience in a technical or quantitative field.
Preferred Qualifications
  • Experience with shipping ML features and products
  • Strong verbal and written communications skills with demonstrated experience in authoring & presenting analytical insights via papers & presentations.
  • Self‑motivated and curious with creative and critical thinking capabilities and drive to figure out and improve how things work.
  • High tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
  • Experience with large scale training ML models including deep learning based models.
  • Experience with GPU‑based distributed training & evaluation.
  • Background in Computer Vision (image augmentation), Audio and Natural Language Processing.
Compensation & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $142,300 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Equal Opportunity & Accessibility

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976