ZipRecruiter

Log In

1

Deep Learning Compression Jobs (NOW HIRING)

AAA Global

Machine Learning Researcher

Miami, FL · On-site

Implement signal compression and combination techniques using ML tools * Implement state-of-the-art machine learning algorithms and design deep learning architectures * Develop model frameworks for ...

Ambarella

$161K - $182K/yr

You will be responsible to build and deploy state of the art deep learning models onto the ... Familiarity with compression techniques like QAT, pruning (nice to have) * Containerization ...

webAI

AI Research Scientist

Austin, TX · On-site

... compression, and on-device deployment • Prototype novel model architectures, training methods ... in deep learning, generative AI, and distributed ML • Analyze experimental results and ...

AIcadium

Sr. Research Data Scientist

San Diego, CA · On-site

$150K - $180K/yr

Research, prototype, and develop state-of-the-art computer vision and deep learning models spanning ... compression, quantization, ONNX, TensorRT, or latency optimization. About Us: Aicadium is a global ...

previous page

Showing results 41-60

All JobsTechnology JobsDeep Learning Compression Jobs

Deep Learning Compression information

See salary details

$11K

$83.9K

$140K

How much do deep learning compression jobs pay per year?

As of Sep 9, 2026, the average yearly pay for deep learning compression in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is deep learning compression?

Deep learning compression refers to techniques used to reduce the size, memory footprint, and computational requirements of deep neural networks without significantly sacrificing their performance. This is important for deploying models on resource-constrained devices such as smartphones or embedded systems. Common methods include pruning, quantization, knowledge distillation, and low-rank factorization. These approaches help make deep learning models more efficient and practical for real-world applications.

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

To thrive as a Deep Learning Compression Engineer, you need a strong background in deep learning, machine learning, and mathematics, typically supported by a degree in computer science or a related field. Proficiency with frameworks like TensorFlow or PyTorch, experience with model compression techniques (such as pruning, quantization, and knowledge distillation), and familiarity with hardware accelerators are essential. Strong problem-solving skills, attention to detail, and effective communication help you innovate and collaborate with research and engineering teams. These skills are critical for developing efficient AI models that meet performance and resource constraints in real-world applications.

What are the typical challenges faced when working on deep learning compression projects?

Professionals in deep learning compression often encounter challenges balancing model size reduction with maintaining high accuracy. Adapting compression techniques—such as pruning, quantization, or knowledge distillation—to different architectures and datasets requires both strong technical knowledge and experimentation. Collaboration with data scientists and software engineers is common, as solutions must be integrated into production systems without sacrificing performance. Staying up to date with rapid advances in compression research is also essential to remain effective and innovative in this role.

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

AspectDeep Learning CompressionMachine Learning Engineer
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, AI, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, tech companies focusing on model optimizationSoftware development teams, AI startups, tech firms building ML applications
Industry UsageAI model deployment, edge computing, mobile AI applicationsDeveloping ML models, data analysis, AI product development

Deep Learning Compression focuses on reducing model size and improving efficiency of neural networks, often for deployment on limited hardware. Machine Learning Engineers develop, train, and optimize ML models across various applications. While both roles require knowledge of AI and neural networks, Deep Learning Compression specializes in model optimization techniques, whereas Machine Learning Engineers work broadly on model development and deployment.

What other helpful pages are available for Deep Learning Compression?

Other pages related to Deep Learning Compression:

Infographic showing various Deep Learning Compression job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Video Codec Machine Learning Engineer, Audio & Media Technologies

San Diego, CA • On-site

Apple
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Appleexternal

$142K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 14 days ago

Key responsibilities

  • Research and develop novel video codecs, focusing on machine learning and AI-powered approaches.

  • Contribute groundbreaking algorithms and ML-driven innovations to the next generation of video coding standards.

  • Partner with software and hardware teams to define, architect, and implement video coding and machine learning algorithms across Apple's products and platforms.

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Imagine the possibilities that await you here! At Apple, bold ideas rapidly transform
into groundbreaking products, services, and customer experiences that shape the
world. Are you someone who brings passion, dedication, and a drive to push bound-
aries? If so, we want to hear from you. We are seeking exceptional talent to join us in
defining the future of video. Our team is at the forefront of crafting the next genera-
tion video codec that will redefine the industry landscape and set new standards for
how the world experiences video. This is your opportunity to make a lasting impact
on both Apple's ecosystem and the broader industry as a whole. Driven by this mis-
sion, our team develops cutting-edge video coding, processing, machine learning,
and systems engineering technologies that power intelligent and immersive video
experiences across Apple's iconic products and platforms, including Photos, Cam-
era, Spotlight, FaceTime, AirPlay, Sidecar, and Apple TV. You will collaborate with a
team of highly driven and talented specialists, working together to turn visionary
codec innovations into transformative technologies that reach and inspire millions of
people every day.
Description
This position is ideal for a highly self-motivated and visionary individual with a deep passion for pushing the boundaries of video coding, machine learning, and AI-driven video technologies.","responsibilities":"Leading and Inspiring a Technical Team: Guiding a team of talented specialists in researching and developing novel video codecs, with a strong emphasis on machine learning and AI-powered approaches, tailored to Apple's unique and innovative use cases.
Shaping the Future of Industry Standards: Spearheading efforts to contribute groundbreaking algorithms and ML-driven innovations to the next generation of video coding standards, positioning Apple at the forefront of the industry.
Driving Cross-functional Collaboration: Partnering closely with software and hardware teams to define, architect, and implement cutting-edge video coding and machine learning algorithms, bringing them to life across Apple's iconic products and platforms.
Advancing ML and Generative Video Technologies: Exploring and applying the latest advancements in deep learning, neural video compression, generative AI, and computer vision to unlock new possibilities in video coding and processing.
Preferred Qualifications
Machine Learning and AI Fluency: Strong understanding and practical experience in applying machine learning, deep learning, and generative AI techniques to video and image processing, coding, and computer vision challenges. Experience with ML-based codec design, neural video compression, or AI-powered video enhancement is highly valued
Visionary and Innovative Mindset: Passion for staying at the cutting edge of machine learning, generative video technologies, and computer vision, with the ability to translate emerging research into real-world product impact
Leadership and Collaboration: Proven experience in leading teams and driving complex projects from concept to completion, with strong written and verbal communication skills to effectively influence and inspire across cross-functional teams.
Minimum Qualifications
A Ph.D degree in Electrical Engineering or Computer Science is required.
Deep Expertise in Video and Image Coding: Comprehensive mastery of video and image coding principles, algorithms, and techniques, with a strong foundation in both classical and ML-driven approaches.
Proficiency in Video Coding Standards: In-depth hands-on experience with industry-leading video coding standards, including H.264/AVC, H.265/HEVC,
AV1, H.266/VVC, and the emerging AV2, with a keen interest in how machine learning is revolutionizing these standards.
Strong Software Engineering Skills: Excellent software design, development,
and debugging skills with proficiency in C/C++, complemented by experience in
ML frameworks such as PyTorch or TensorFlow.
Pay & 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

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

View All Apple Jobs

Apply