Mid Level Deep Learning Engineer Jobs
Mid level deep learning engineer jobs go to engineers ready to own model development end to end, drive architecture decisions with limited oversight, and mentor junior teammates through complex implementation challenges. Roles are a mix of on-site, remote, and hybrid across Technology & Software, Electronics & Hardware, and Artificial Intelligence, with employers like NVIDIA hiring at this level now.
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Showing 5 of 8+ Mid Level Deep Learning Engineer jobs
INTRODUCTION
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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Time and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.
ROLE AND RESPONSIBILITIES
What You'll Be Doing
- Analyzing deep learning networks and developing compiler optimization algorithms.
- Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
- Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.
BASIC QUALIFICATIONS
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Ability to work independently, define project goals and scope, and lead your own development efforts.
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.
PREFERRED QUALIFICATIONS
- Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.
- Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.
- Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.
- GPU kernel generation with high performance and fast build time.
- A track record of success in mentoring junior engineers and interns is a bonus.
COMPENSATION
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
deeplearning, JR2016814
INTRODUCTION
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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Time and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.
ROLE AND RESPONSIBILITIES
What You'll Be Doing
- Analyzing deep learning networks and developing compiler optimization algorithms.
- Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
- Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.
BASIC QUALIFICATIONS
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Ability to work independently, define project goals and scope, and lead your own development efforts.
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.
PREFERRED QUALIFICATIONS
- Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.
- Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.
- Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.
- GPU kernel generation with high performance and fast build time.
- A track record of success in mentoring junior engineers and interns is a bonus.
COMPENSATION
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
deeplearning, JR2016814
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Mid Level Deep Learning Engineer Jobs: Frequently Asked Questions
How do I get a mid level deep learning engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you led model design, debugged production systems, or improved performance metrics with minimal guidance. Applications that show end-to-end delivery, clear technical judgment, and cross-functional collaboration stand out at this level. Tailor your resume to the specific domain the role targets, whether that is computer vision, NLP, or generative AI.
Which companies hire mid level deep learning engineers?
Companies hiring mid level deep learning engineers right now include NVIDIA, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, including technology product companies, applied research labs, and enterprise organizations building proprietary AI systems.
Are there remote mid level deep learning engineer jobs?
Yes, remote and hybrid availability is strong at this level. About 0% of mid level deep learning engineer openings are remote or hybrid as of November 2026, reflecting how extensively the field has adopted distributed team structures. On-site roles tend to cluster around research-heavy environments or hardware-integrated projects where in-person collaboration is a practical requirement.
How do I move up to a mid level deep learning engineer role?
Moving from entry level to mid level takes deliberate progression beyond task completion. Build depth in a core area such as model training pipelines, optimization, or deployment, then seek opportunities to own a feature or project from design through production. Demonstrating measurable impact, like improving inference speed or reducing error rates, and taking initiative without waiting for direction signals readiness for mid level responsibility.
Which industries hire the most mid level deep learning engineers?
Mid Level deep learning engineer roles concentrate in Technology & Software, Electronics & Hardware, and Artificial Intelligence, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they are actively scaling AI-powered products and need engineers who can operate independently on mission-critical model development, not just support senior staff.