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Deep Learning Scientist Jobs in California (NOW HIRING)

Steg.AI

Machine Learning Scientist

Irvine, CA · On-site

$140 - $200/hr

AI is a National Science Foundation (NSF) and investor-funded startup based in Orange County ... Expert with PyTorch and training and testing deep learning models* Familiarity with dataset ...

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180 - $270/hr

About Tacit We are an early-stage, deep tech startup based in San Francisco, developing innovative ... As a Machine Learning Scientist, you will develop cutting‑edge AI models to integrate and decode ...

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180K - $270K/yr

About Tacit We are an early-stage, deep tech startup based in San Francisco, developing innovative ... About the role As a Machine Learning Scientist , you will develop cutting-edge AI models to ...

KLA

Algorithm Engineer - Deep Learning

Milpitas, CA · On-site

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Design deep learning and GenAI models to meet modeling requirements. * Implement modeling ...

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Deep Learning Scientist information

See California salary details

$37K

$121.1K

$193.9K

How much do deep learning scientist jobs pay per year?

As of Aug 24, 2026, the average yearly pay for deep learning scientist in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a deep learning scientist?

Deep Learning Scientists are experts who design, develop, and implement advanced machine learning models inspired by the structure and function of the brain, known as artificial neural networks. They work with large datasets to train algorithms that can recognize patterns, make predictions, and solve complex problems in areas such as image recognition, natural language processing, and autonomous systems. Deep Learning Scientists often collaborate with software engineers, data scientists, and domain specialists to deploy models in real-world applications like healthcare, finance, and self-driving cars.

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

To thrive as a Deep Learning Scientist, you need a solid background in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and proficiency in Python are typically required. Strong problem-solving skills, creativity, and the ability to communicate complex ideas clearly set outstanding candidates apart. These capabilities are essential for developing innovative AI solutions, interpreting results, and collaborating effectively in multidisciplinary teams.

What are some typical challenges faced when working as a deep learning scientist, and how can they be addressed?

Deep Learning Scientists often encounter challenges such as managing large datasets, tuning complex model architectures, and ensuring reproducibility of experiments. Handling these issues requires strong skills in data preprocessing, familiarity with version control systems, and experience with frameworks like TensorFlow or PyTorch. Collaborating closely with cross-functional teams—including data engineers, software developers, and domain experts—can also help in overcoming technical and project-related obstacles. Continuous learning and staying updated with the latest research is essential to excel in this rapidly evolving field.

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

AspectDeep Learning ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; strong background in deep learning frameworksBachelor's or Master's in Computer Science or related fields; proficiency in machine learning algorithms and software engineering
Work EnvironmentResearch-focused, experimental, often in R&D teamsDevelopment and deployment-focused, working on production systems
Employer & Industry UsageTech companies, research labs, AI startupsTech firms, finance, healthcare, and industries deploying ML models

While both roles involve machine learning, Deep Learning Scientists focus on developing advanced neural network models and research, whereas Machine Learning Engineers implement, optimize, and deploy these models in real-world applications.

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

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

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

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

Deep Learning Scientist jobs near you
Infographic showing various Deep Learning Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Deep Learning Scientist, Speech Synthesis

Vailexa

Santa Clara, CA • On-site

Other

Re-posted 3 days ago

Job description

Build More Than Just a Career. Build Your Future. At Vailexa, we’re not just hiring — we’re building thinkers, creators, and future leaders. We believe in giving people the space to grow, the freedom to think, and the opportunity to create real impact from day one. If you’re someone who wants to learn fast, take ownership, and grow beyond limits, you’ll feel right at home here. Key Responsibilities Train speech synthesis mel spectrogram and vocoder models Measure and benchmark model performance across use cases Maintain and enhance text to speech evaluation systems Analyze model accuracy and bias and recommend improvements Improve processes related to speech data preparation, augmentation, and filtering Develop and refine training datasets for speech models Characterize performance and quality metrics across different platforms Collaborate with cross functional teams to deliver new product features Participate in code development, design reviews, and test planning Identify issues, propose solutions, and contribute to continuous innovation Required Qualifications Master’s degree or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Linguistics, or Computational Linguistics or equivalent experience Minimum of 5 years of relevant experience Strong programming skills in Python Solid understanding of programming fundamentals and software design Deep knowledge of machine learning and deep learning techniques including CNN, RNN, LSTM, and Transformers Experience applying deep learning to speech synthesis, large language models, and speech to speech translation Hands on experience with speech technologies such as speech synthesis and voice cloning Experience training speech models Proficiency with PyTorch deep learning frameworks Knowledge of speech signal processing techniques including FFT, MFCC, and mel spectrograms Familiarity with version control tools such as Git, Gerrit, or GitLab Strong collaboration and communication skills in a matrixed environment Preferred Qualifications Fluency in one or more languages such as Spanish, Mandarin, German, Japanese, Russian, French, Arabic, Hindi, Korean, Italian, or Portuguese Experience with multilingual or code switched text to speech systems Experience with voice cloning and cross lingual voice cloning Knowledge of text normalization and inverse text normalization using neural networks or WFST Experience working with grapheme to phoneme systems for multiple languages Interest in linguistics, phonetics, and language technologies Strong C plus plus programming skills Familiarity with GPU technologies such as CUDA, cuDNN, or TensorRT Experience deploying machine learning models to cloud, data center, or embedded systems Ready to take the next step? If you’re excited about this role and ready to grow with a team that values ambition, ideas, and impact — we’d love to hear from you. Apply now and start building your journey with Vailexa.

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