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Deep Learning Engineer Jobs (NOW HIRING)

Quidient

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Bot Auto

Intern, Deep Learning Engineer

Houston, TX

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

Quidient

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

NBCUniversal

Staff Deep Learning Engineer

Manhattan, NY · On-site

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision ...

NBCUniversal

Staff Deep Learning Engineer

Manhattan, NY · On-site

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision ...

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Deep Learning Engineer information

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$115.9K

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How much do deep learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for deep learning engineer in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

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 does a deep learning engineer do?

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 skills and qualifications does a deep learning engineer need?

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.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.
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Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

Deep Learning Manipulation Engineer

Pittsburgh, PA • On-site

Skild AI
See more jobs at Skild AIexternal

$100K - $300K/yr

Full-time

Re-posted 12 days ago

Job description

Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a Deep Learning Engineer to develop and refine models for robotic manipulation. You will design, train, and deploy algorithms that enable robots to interact intelligently and adapt to their environments. Working closely with our machine learning, robotics, and research teams, you'll ensure these models are robust, efficient, and ready for real-world challenges. Your work will directly advance Skild AI's robotics capabilities, enabling robots to perform complex tasks autonomously.
Responsibilities
  • Design, implement, and optimize deep learning models for robotic manipulation.
  • Model robotic manipulation processes to enable analysis, simulation, planning, and controls
  • Collaborate with cross-functional teams to develop scalable and generalizable manipulation solutions for deployment in robotic systems.
  • Work with inference, deployment, and application teams to integrate deep learning models seamlessly into robotic platforms.
Preferred Qualifications
  • BS, MS, or higher degree in Computer Science, Robotics, Mechanical Engineering, or a related field, or equivalent practical experience.
  • Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Proficiency with advanced deep learning techniques and architectures as well as reinforcement learning and or imitation learning.
  • Experience with distributed deep learning systems.

Base Salary Range
$100,000-$300,000 USD

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