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Research Assistant Deep Learning Jobs in California

pony.ai

Research Intern - Deep Learning

Fremont, CA

$7.0K - $10K/mo

Experience with deep learning research and tools. * Proficiency in software design and development using Python and C++. * Experience working with large-scale datasets, data preprocessing, and ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Experience with deep learning research and tools. * Proficiency in software design and development using Python and C++. * Experience working with large-scale datasets, data preprocessing, and ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Experience with deep learning research and tools. * Proficiency in software design and development using Python and C++. * Experience working with large-scale datasets, data preprocessing, and ...

Pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Experience with deep learning research and tools. * Proficiency in software design and development using Python and C++. * Experience working with large-scale datasets, data preprocessing, and ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

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 ...

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Research Assistant Deep Learning information

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

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

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.
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Research Assistant Deep Learning jobs near you
Infographic showing various Research Assistant Deep Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Research Intern - Deep Learning

pony.ai

Fremont, CA

$7.0K - $10K/mo

Internship

Re-posted yesterday

Job description

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites around the world. Operating Robotaxi, Robotruck and Personally Owned Vehicles (POV) business units, Pony.ai is an industry leader in the commercialization of autonomous driving and is committed to developing the safest autonomous driving capabilities on a global scale. Pony.ai's leading position has been recognized, with CNBC ranking Pony.ai #10 on its CNBC Disruptor list of the 50 most innovative and disruptive tech companies of 2022. In June 2023, Pony.ai was recognized on the XPRIZE and Bessemer Venture Partners inaugural "XB100" 2023 list of the world's top 100 private deep tech companies, ranking #12 globally. As of August 2023, Pony.ai has accumulated nearly 21 million miles of autonomous driving globally. Pony.ai went public at NASDAQ in November 2024.

Responsibility
  • Work with experts in the field of self-driving vehicles on designing and developing large-scale foundation models trained on vast amounts of real world data.
  • Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to data pipelines; and streamline them to run in real-time on the cars.
  • Develop and deploy deep learning models, including vision language models (VLMs) and Large Language Models (LLMs)
  • Design and implement multi-modality and multi-task perception models focusing on 3D object detection and tracking, segmentation, semantics understanding, video understanding, scene understanding, traffic control, or trajectory prediction, etc.
  • Optimize deep learning models to run robustly under tight run-time constraints.

Requirements

  • Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field
  • Strong background in deep learning, with experience in model design, training and evaluation.
  • Experience with deep learning research and tools.
  • Proficiency in software design and development using Python and C++.
  • Experience working with large-scale datasets, data preprocessing, and pipeline management.

Preferred Experience

  • Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI
  • Experience in applying ML/DL for behavior prediction, imitation learning, motion planning.
  • Experience in deploying deep learning algorithms for real time applications, with limited computing resources.
  • Experience in convex optimization, computational geometry or linear algebra.
  • Experience in GPU/CUDA/TensorRT
  • Previous internships involving large-scale deep learning models and systems
  • Preferred graduate before Dec 2026

Note

  • This position is rolling based and it can start any time.
  • This position is fully onsite in Fremont, at least 3 months.

Compensation

  • Master: $7000/month
  • PhD: $10,000/month

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