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Deep Learning Ai Jobs in California (NOW HIRING)

Hayden AI

Deep Learning Engineer

San Francisco, CA · On-site

$161K - $175K/yr

About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the ... About the Deep Learning Team The Deep learning team's work is at the crux of Hayden AI's solutions ...

pony.ai

Research Intern - Deep Learning

Fremont, CA

$7.0K - $10K/mo

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous ... Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous ... Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous ... Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ...

Pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous ... Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ...

Hayden AI

Staff Deep Learning Engineer

San Francisco, CA · On-site

$230K - $299K/yr

About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the ... About the Role As a Staff Deep Learning Engineer in the Deep Learning team at Hayden, you are a ...

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 ...

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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 86% Full Time, and 14% Contract. Highlights an 79% In-person, and 21% Remote job distribution.

Deep Learning Engineer

Hayden AI

San Francisco, CA • On-site

$161K - $175K/yr

Full-time

Re-posted 3 days ago

Job description

About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
About the Deep Learning Team
The Deep learning team's work is at the crux of Hayden AI's solutions to its customers. The team is responsible for building and maintaining advanced models that are able to perceive the world and the knowledge produced by the models is used downstream to implement various customer use-cases. The team runs a number of models both in the cloud as well as on the edge device serving different scenarios. The team also works closely with the platform team to build out Hayden AI's MLOps infrastructure to achieve better scale and reliability.
About the Role
As a Deep Learning Engineer at Hayden, you will make key contributions towards building foundational AI capabilities for Hayden that will enable solving complex problems for Hayden AI Customers. In this role, you will build, train, evaluate and deploy state of the art ML models in production at scale. You will report into the Director of AI within the Perception Org and work closely with other engineering as well as product teams to deliver value to Hayden AI customers. We are looking for someone who has familiarity with or growing expertise in at least one of the verticals below - depth in a specific area is valued but not required on day one.
  1. 3D vision models to predict depth and 3D structure,
  2. Video/temporal behavior models to predict intent,
  3. Deep understanding of Vision language models and hands-on experience fine tuning them,
  4. Deep understanding of foundation models in perception.
  5. Deep knowledge of Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models

This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.
Key Responsibilities
Below are your primary responsibilities. These represent the core areas where you'll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.
  • Come up with solutions to complex problems in perception using deep learning.
  • Articulate ideas both verbally and in written form culminating in clear design and project plan docs for their work
  • Contribute to team roadmap and planning
  • Work with cross functional teams across the company and contribute towards delivery of end to end solutions for the customer

Required Qualifications
The qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.
  • Experience: 1-2 years experience building and deploying machine learning models for perception in production settings.
  • Core Skills: Solid hands-on experience designing, training, and evaluating machine learning models for perception. Demonstrated ability to independently build ML pipelines and deploy models to cloud environments (AWS, GCP, or Azure); familiarity with MLOps practices including experiment tracking, model versioning, and automated workflows. Hands-on experience in PyTorch, Python, and related skills.
  • Personal Attributes:Good communicator, self starter and ability to collaborate with others, quick learner who can adapt to a fast paced startup culture
  • Education: Bachelors or Masters in Computer Science or related field
  • Nice to Have: Experience working in perception problems in self driving car companies that aligns closely with the work of this team.

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