ZipRecruiter

Log In

1

Deep Learning Scientist Jobs in California (NOW HIRING)

Spotter

Machine Learning Scientist

Culver City, CA · Remote

Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production machine learning models, particularly in areas such as ...

PlusAI

Deep Learning Intern

Santa Clara, CA · On-site

$19 - $65/hr

Required Skills: * Pursuing MS or PhD in Computer Science, Electrical Engineering, Robotics ... Past experiences in deep learning projects involving object detection, motion tracking or semantic ...

PlusAI

Deep Learning Intern

Santa Clara, CA

$19 - $65/hr

Required Skills: * Pursuing MS or PhD in Computer Science, Electrical Engineering, Robotics ... Past experiences in deep learning projects involving object detection, motion tracking or semantic ...

Spotter

Machine Learning Scientist

Culver City, CA · On-site

For more information about Spotter, please visit Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Masters in Computer Science, Software Engineering, Mathematics, or equivalent * Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs, or implement a ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Masters in Computer Science, Software Engineering, Mathematics, or equivalent * Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs, or implement a ...

Matroid

Deep Learning Engineer

Palo Alto, CA

$170K - $300K/yr

Masters in Computer Science, Software Engineering, Mathematics, or equivalent * Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs, or implement a ...

next page

Showing results 1-20

All JobsDeep Learning Scientist JobsDeep Learning Scientist Jobs in California

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 Jul 20, 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 are the key skills and qualifications needed to thrive as a Deep Learning Scientist, and why are they important?

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 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 Deep Learning Scientists?

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.

Will MLE be replaced by AI?

As a Deep Learning Scientist, machine learning engineering (MLE) involves designing and deploying models, which AI advancements can automate or enhance. However, MLE roles require expertise in data handling, model optimization, and domain knowledge that AI tools support but do not fully replace. Human oversight remains essential for ensuring model accuracy, ethical considerations, and system integration.

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.

Which 3 jobs will survive AI?

Deep Learning Scientists are likely to continue to be in demand as AI advances, especially in research, model development, and complex problem-solving roles. Jobs that require high levels of creativity, emotional intelligence, or physical dexterity, such as healthcare professionals, skilled trades, and creative artists, are also expected to persist. Combining technical skills with domain expertise will enhance job security in an AI-driven future.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Scientist or AI executive, with compensation including salary, bonuses, and stock options. These roles often require advanced expertise in machine learning, deep learning frameworks, and extensive industry experience, and they are usually found in leading tech companies or AI-focused organizations.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like Deep Learning Scientist, are generally well-paid due to the specialized skills required, such as programming in Python, experience with neural networks, and knowledge of frameworks like TensorFlow or PyTorch. Salaries vary based on experience, location, and industry, but these roles tend to offer above-average compensation compared to many other tech jobs.
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 July 2026, with employment types broken down into 74% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.
Deep Learning Scientist, Speech Synthesis

Deep Learning Scientist, Speech Synthesis

Catapult Solutions Group

Santa Clara, CA • On-site, Remote

Contractor

Posted 25 days ago

Job description

Deep Learning Scientist - Speech Synthesis
Location: 100% Remote (Anywhere in the U.S.)
Duration: 6-Month Contract
Position Overview
We are seeking a Deep Learning Scientist - Speech Synthesis to support the development of next-generation speech AI technologies. This role focuses on training and optimizing speech models, improving model performance, and solving complex machine learning challenges related to speech applications.
The ideal candidate has strong experience in speech synthesis (Text-to-Speech) or Speech-to-Text, deep learning, and Python development. Success in this role requires the ability to analyze model behavior, diagnose training issues, and improve model performance-not just collect or evaluate data.
Key Responsibilities
  • Train and optimize speech synthesis models, including mel spectrogram and vocoder models.
  • Analyze training metrics, validation losses, and model performance to identify root causes of model issues and recommend improvements.
  • Benchmark and optimize speech models across multiple use cases.
  • Improve speech data preparation, augmentation, filtering, and dataset quality.
  • Develop and refine high-quality training datasets for speech AI models.
  • Measure and characterize model accuracy, quality, and bias.
  • Collaborate with cross-functional teams to develop and deliver new speech AI features.
  • Participate in software development, design reviews, testing, and code reviews.
  • Troubleshoot technical issues and contribute to continuous model improvements.
Required Qualifications
  • Master's degree or Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Linguistics, Computational Linguistics, or a related field (or equivalent experience).
  • 3+ years of relevant industry experience.
  • Strong Python programming skills.
  • Strong understanding of machine learning and deep learning concepts.
  • Experience with Text-to-Speech (TTS), Speech Synthesis, or Speech-to-Text (STT) technologies.
  • Hands-on experience training deep learning models using PyTorch.
  • Ability to analyze training behavior, validation losses, and model performance to troubleshoot and improve machine learning models.
  • Knowledge of speech signal processing concepts, including FFT, MFCC, and mel spectrograms.
  • Strong understanding of software development fundamentals.
  • Experience using version control systems such as Git, Gerrit, or GitLab.
  • Excellent communication and collaboration skills.
Preferred Qualifications
  • Experience with deep learning architectures such as CNNs, RNNs, LSTMs, and Transformers.
  • Experience with voice cloning or multilingual speech systems.
  • Knowledge of text normalization (TN), inverse text normalization (ITN), or grapheme-to-phoneme (G2P) systems.
  • Fluency in one or more languages such as Spanish, Mandarin, German, Japanese, Russian, French, Arabic, Hindi, Korean, Italian, or Portuguese.
  • Interest in linguistics, phonetics, and speech technologies.
  • Strong C++ programming skills.
  • Familiarity with GPU technologies such as CUDA, cuDNN, or TensorRT.
  • Experience deploying machine learning models to cloud, data center, or embedded environments.
What We're Looking For
The ideal candidate is someone who enjoys solving difficult machine learning problems and has hands-on experience training speech models. Beyond building models, we're looking for someone who can investigate why a model is underperforming, analyze validation losses, identify root causes, and improve overall model quality and performance.
Additional Information
  • 100% remote position within the United States.
  • No specific U.S. time zone requirement.
  • This is a contract opportunity.
  • Opportunity to contribute to cutting-edge speech AI and deep learning technologies.

Apply