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Pytorch Developer Jobs in San Antonio, TX (NOW HIRING)

CACI

Machine Learning Engineer

San Antonio, TX · Hybrid

Deep knowledge of ML frameworks such as PyTorch or TensorFlow. Programming: Strong Python. ML libraries including Spark MLlib, Scikit-learn, XGBoost, Keras, Hugging Face, PyTorch Geometric, MLflow.

Addison Group

AI.ML Engineer (Google)

San Antonio, TX · On-site

$125K/yr

Strong experience with GCP services, Python, and ML frameworks such as TensorFlow, PyTorch, or scikit-learn. * Experience with Generative AI, LLMs, prompt engineering, and RAG architectures.

Catalyst Labs

ML Engineer

San Antonio, TX · On-site

... PyTorch or TensorFlow. • Familiarity with cloud environments and infrastructure (preferably AWS). • Strong understanding of data pipeline design, real-time inference, and model monitoring. • ...

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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 San Antonio, TX?

For Pytorch Developer jobs in San Antonio, TX, the most frequently searched job titles are:

What job categories do people searching Pytorch Developer jobs in San Antonio, TX look for?

The top searched job categories for Pytorch Developer jobs in San Antonio, TX are:

What cities near San Antonio, TX are hiring for Pytorch Developer jobs?

Cities near San Antonio, TX with the most Pytorch Developer job openings:

Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in San Antonio, TX as of August 2026, with employment types broken down into 83% Full Time, 6% Part Time, and 11% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Senior AWS Bedrock & SageMaker Developer

Programmers.io

San Antonio, TX • On-site

Contractor

Re-posted 12 days ago

Job description

Descriptions:
"• Develop, integrate, and optimize Generative AI applications using AWS Bedrock, including prompt engineering, RAG implementation, and AI agent workflows.
• Create and optimize prompts for LLMs
• Work with Amazon Bedrock APIs for model inference
• Develop backend services using Python / Node.js
• Enable real-time and streaming AI responses
• Build AI solutions using Bedrock Knowledge Bases
• Integrate with data sources (S3, databases, enterprise systems)
• Implement vector search and embeddings
• Design and build AI agents using Bedrock Agents
• Implement multi-step workflows and task automation
• Integrate external APIs/tools into AI workflows
• Work with core AWS services:
o IAM (security & access control)
o S3 (data storage)
o Lambda (serverless compute)
o API Gateway (service exposure)
• Deploy scalable and secure AI solutions
• Implement guardrails and content filtering
• Ensure data privacy, compliance, and safe AI usage
• Optimize token usage and model selection
• Monitor and control Bedrock usage costs
• Convert business requirements into AI-driven solutions
• Manage and utilize SageMaker Feature Store for reusable feature engineering
• Monitor model performance and detect data drift in production systems
• Maintain and retrain models for continuous performance improvement
• Track experiments, metrics, and ensure model reproducibility
• Integrate SageMaker with AWS services like S3, IAM, Lambda, and CloudWatch
• Optimize infrastructure, performance, and cost of ML workloads
• Collaborate with cross-functional teams to design and deliver ML solutions"
"Generative AI & LLM Fundamentals, Prompt Engineering, Bedrock API and SKD usage, RAG, AI Agents and workflow design,
Programming skill (Python, APIs, Microservice), AWS core knowledge (IAM, S3, Lambda, API Gateway), Application integration skills, Vector databases, CI/CD for AI Apps.
Understanding of ML life cycle, Strong coding in Python, Good knowledge on Py libraries (Pandas, Numpy, Scikit-learn (ML), Tensorflow/PyTorch),
Exploratory Data Analysis (EDA), Handling large dataset in Amazon S3, Model Training and Optimization, Model deployment, MLOps & Pipeline Automation.
Hands on SageMaker Studio, Training Jobs, Endpoints, Pipeline, Model registry, Feature Store
Hands on AWS Core services (S3, IAM, EC2, Lambda, Cluodwatch)"
Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Digital : DevOps~Github Enterprise
Experience Required: 10 & Above