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Deep Learning Ai Jobs in California (NOW HIRING)

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

About the Role As a Deep Learning Engineer, you will: * Design, develop, and deploy deep-learning ... Experience in hybrid AI / DSP algorithm development is a plus but not required. * A passion for ...

Toyon

Deep Learning Algorithm Developer

Goleta, CA · On-site

$120K - $200K/yr

Our researchers apply AI/ML techniques to develop data processing automation solutions for problems ... Requirements Candidates for the Deep Learning Algorithm Developer position should have a strong ...

Nvidia

Deep Learning Compiler Engineer

Santa Clara, CA · On-site

Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era ... NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs ...

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Deep Learning Ai information

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

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

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

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

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What are popular job titles related to Deep Learning Ai jobs in California?

For Deep Learning Ai jobs in California, the most frequently searched job titles are:

What job categories do people searching Deep Learning Ai jobs in California look for?

The top searched job categories for Deep Learning Ai jobs in California are:

What cities in California are hiring for Deep Learning Ai jobs?

Cities in California with the most Deep Learning Ai job openings:

Deep Learning Ai jobs near you
Infographic showing various Deep Learning Ai job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Audio Deep Learning Engineer

femtoAI

San Bruno, CA • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 27 days ago

Job description


About the Role
As a Deep Learning Engineer, you will:
  • Design, develop, and deploy deep-learning-based and classical DSP audio algorithms for our SPU platform.
  • Leverage innovative model compression techniques to optimize performance-per-joule on custom silicon.
  • Be a core contributor to our deep learning and DSP development platform, advancing novel algorithms for audio processing.
  • Collaborate directly with customers across diverse industries to deliver impactful solutions and exciting new features.

This is a unique opportunity to work on challenging problems at the intersection of deep learning, model optimization, and embedded systems, while driving real-world impact in industries ranging from consumer electronics to automotive and beyond.
What You'll Do
  • Develop and optimize deep learning models for audio processing, including tasks like speech enhancement, beamforming, event detection, sound localization, voice identification, voice interfaces, noise reduction, echo cancellation, feedback cancellation, and more.
  • Drive innovation in model efficiency, compression, and deployment on embedded platforms.
  • Leverage multi-sensor data to improve algorithm performance in difficult environments.
  • Work closely with customers to understand their needs and tailor solutions to meet their goals.
  • Contribute to the end-to-end process of model development, from research and prototyping to deployment on hardware.

Requirements
  • 3+ years of relevant experience in deep learning and/or DSP engineering.
  • Strong experience with Python and PyTorch (or other deep learning frameworks).
  • A background in Computer Science, Mathematics, Electrical Engineering or a related field (BS, MS, PhD, or equivalent work experience).
  • Experience in hybrid AI / DSP algorithm development is a plus but not required.
  • A passion for solving challenging problems and collaborating in a fast-paced, innovative environment.

Desired Skills and Experience
Deep learning, Machine learning, DSP, Python, PyTorch
Benefits
  • 401(k)
  • Medical insurance
  • Vision insurance
  • Dental insurance
  • Commuter benefits
  • Disability insurance
  • Paid maternity leave
  • Paid paternity leave
  • Child care support

femtoAI is an equal opportunity employer committed to a diverse workforce which strives to create an inclusive working environment empowering everyone to do their best work. We do not discriminate on the basis of race, ethnicity, religion, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.

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