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Pytorch Developer Jobs in Hawthorne, CA (NOW HIRING)

Gallatin AI, Inc.

AI Software Engineer

El Segundo, CA · On-site

The AI Software Engineer will develop and deploy AI-powered solutions, working across the full AI ... PyTorch, TensorFlow, CUDA, Jupyter Notebooks, Large Language Models (LLMs) and Open-Source Models ...

Programmers.io

Data Architect with AWS

Torrance, CA · On-site

$66.50 - $85.50/hr

Familiarity with PyTorch, TensorFlow, or LangChain for integrating AI into enterprise workflows. · ... or AWS Certified Data Engineer). · Analytics Background: Proven track record of designing ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in ... Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch

The Walt Disney Company

Sr Software Engineer

Glendale, CA · On-site

$135K - $181K/yr

Hands-on expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data pipelines. * Hands-on building and deploying LLM-based applications, including prompt engineering and fine ...

SAIC

Senior Principal AI/ML Systems Engineer

El Segundo, CA · On-site +1

$160K - $200K/yr

Strong knowledge of ML frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R). * Experience with cloud computing services (e.g., AWS, Azure, Google Cloud) and their AI/ML ...

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Pytorch Developer information

What is a PyTorch developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are some common challenges PyTorch developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.

What are the key skills and qualifications needed to thrive as a PyTorch developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are popular job titles related to Pytorch Developer jobs in Hawthorne, CA?

For Pytorch Developer jobs in Hawthorne, CA, the most frequently searched job titles are:

What cities near Hawthorne, CA are hiring for Pytorch Developer jobs?

Cities near Hawthorne, CA with the most Pytorch Developer job openings:

Pytorch Developer jobs near you

AI Software Engineer (Vehicle Engineering)

SpaceX

Hawthorne, CA • On-site

Full-time

Re-posted 18 days ago

SpaceX rating

8.7

Company rating: 8.7 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

16th of 72 rated aerospace companies

Job description

Job Summary:
SpaceX is actively developing technologies to enable human life on Mars. The AI Software Engineer will focus on solving complex AI data problems for launch vehicles and spacecrafts, developing core AI technologies to accelerate engineering and support the rapid reuse of the Falcon launch vehicle.
Responsibilities:
• Design and train highly reliable, scalable AI/ML models that empower engineers across all SpaceX departments
• Design agentic AI systems and multi-agent workflows to perform engineering tasks
• Build and optimize large-scale machine learning training pipelines to create next-generation AI applications that transform day-to-day engineering operations
• Develop and fine-tune foundation models (LLMs, vision models, multimodal systems) for high-impact SpaceX use cases
• Create production-grade AI tools for data analysis, anomaly detection, predictive modeling, and automated decision-making
• Collaborate with peers on AI architecture, model design, training strategies, and code reviews
• Rapidly build and iterate on AI prototypes, rigorously quantifying model performance, accuracy, and technical constraints
• Own the complete AI model lifecycle — from data preparation and training infrastructure to deployment, monitoring, and continuous improvement
• Deep-dive into complex engineering problems to identify and implement efficient, custom-trained AI solutions
• Establish rigorous AI standards for model validation, safety, reliability, bias mitigation, and data security
• Ensure all AI systems undergo thorough testing and validation to deliver accurate, trustworthy, and production-ready outputs
Qualifications:
Required:
• Bachelor’s degree in computer science, data science, engineering, math, or physics; OR 4+ years of professional experience building and training AI/ML systems in lieu of a degree
• 1+ years of experience in AI software engineering with a focus on model training, fine-tuning, and machine learning systems
• 1+ years of programming experience in Python
Preferred:
• Expert understanding of LLM transformer architectures and training procedure including pre-training, supervised fine tuning, and reinforcement learning.
• Demonstrated experience training and fine-tuning large language models (LLMs) and other foundation models at scale
• Proven track record training and optimizing machine learning models for computer vision (object detection, segmentation, 3D reconstruction, etc.)
• Deep expertise with modern ML frameworks: PyTorch, TensorFlow, JAX, or equivalent
• Experience designing and running large-scale ML training pipelines, including distributed training on GPU clusters, hyperparameter optimization, and experiment tracking
• Strong understanding of MLOps best practices: model versioning, experiment management (MLflow, Weights & Biases, etc.), CI/CD for ML, and automated retraining
• Strong foundation in statistics, machine learning theory, deep learning architectures, optimization algorithms, and model evaluation
• Proficiency developing on Linux systems
• Solid understanding of version control (Git), testing, continuous integration, deployment, and monitoring for ML systems
• Experience building complex agentic AI systems and multi-agent workflows
• Experience with data infrastructure for training: relational databases (PostgreSQL), non-relational databases, data lakes, and feature stores (vector databases are a plus)
• Experience deploying containerized applications using Docker and Kubernetes
Company:
SpaceX develops and operates rockets, satellite networks, and AI infrastructure including launch, connectivity, and cloud services. Founded in 2002, the company is headquartered in Hawthorne, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

What SpaceX employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About SpaceX

Sourced by ZipRecruiter

Industry

Aerospace product and parts manufacturing, data services, guided missile and space vehicle manufacturing and satellite telecommunications

Company size

1,001 - 5,000 Employees

Headquarters location

Hawthorne, CA, US

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