ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
AI Lead Engineer
Dallas, TX · On-site +1
$101K - $133K/yr
PyTorch * Scikit-learn * Data Preprocessing & Feature Engineering * Model Training, Validation & Evaluation * Statistics & ML Algorithms * MLOps * CI/CD Pipelines * Docker * Kubernetes * REST APIs ...
AI Lead Engineer
Dallas, TX · On-site +1
$101K - $133K/yr
PyTorch * Scikit-learn * Data Preprocessing & Feature Engineering * Model Training, Validation & Evaluation * Statistics & ML Algorithms * MLOps * CI/CD Pipelines * Docker * Kubernetes * REST APIs ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
Model Development Training Design develop and train machine learning and deep learning models using Python and frameworks like TensorFlow Keras or PyTorch * Data Engineering Preprocessing Clean ...
Model Development Training Design develop and train machine learning and deep learning models using Python and frameworks like TensorFlow Keras or PyTorch * Data Engineering Preprocessing Clean ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt Engineering, Workflow Design, and GenAI Optimization. Key ...
Pytorch information
See Dallas, TX salary details
$79.4K - $90.8K
11% of jobs
$101.2K is the 25th percentile. Wages below this are outliers.
$90.8K - $102.1K
16% of jobs
$102.1K - $113.5K
16% of jobs
$113.5K - $124.8K
5% of jobs
$124.8K - $136.2K
0% of jobs
$136.2K - $147.5K
0% of jobs
$147.5K - $158.9K
1% of jobs
The median wage is $159.7K / yr.
$158.9K - $170.2K
22% of jobs
$173.4K is the 75th percentile. Wages above this are outliers.
$170.2K - $181.6K
16% of jobs
$181.6K - $192.9K
3% of jobs
$192.9K - $204.3K
11% of jobs
$79.4K
$142.4K
$204.3K
How much do pytorch jobs pay per year?
What is a PyTorch job?
A PyTorch job typically involves working with the PyTorch deep learning framework to develop, train, and deploy machine learning models. Professionals in this role may build neural networks, perform data preprocessing, optimize models, and integrate them into applications. These jobs are commonly found in AI research, software development, and data science, requiring expertise in Python, deep learning, and model optimization techniques.
What kinds of projects or tasks can a PyTorch developer expect to work on in a typical role?
As a PyTorch developer, you will likely work on developing, refining, and deploying deep learning models for tasks such as image recognition, natural language processing, or recommendation systems, depending on your company's focus. Your responsibilities may include data preprocessing, model architecture design, experimentation, performance tuning, and collaborating with data scientists and software engineers to integrate models into production systems. You might also be called upon to conduct research or prototype new algorithms, keeping up with the latest advancements in the AI field. Projects can vary from quick proofs of concept to large-scale deployments, offering diverse opportunities to grow your technical and collaborative skills.
What are the key skills and qualifications needed to thrive in the PyTorch position, and why are they important?
To thrive in a PyTorch developer role, you need a strong background in deep learning, programming (especially Python), and a solid understanding of machine learning fundamentals, often supported by a degree in computer science, engineering, or a related field. Experience with PyTorch, CUDA, cloud platforms (like AWS or Azure), and familiarity with data processing pipelines are highly valued, and certifications in AI or machine learning can be beneficial. Key soft skills include problem-solving, teamwork, and effective communication to collaborate with cross-functional teams and present technical results clearly. These skills are crucial for building robust machine learning models, ensuring reproducibility, and driving innovation in fast-paced, data-driven environments.
What are popular job titles related to Pytorch jobs in Dallas, TX?
For Pytorch jobs in Dallas, TX, the most frequently searched job titles are:
- Machine Learning Engineer
- Machine Learning Engineer New Grad
- Remote Machine Learning Engineer
- Senior Machine Learning Software Engineer
- Machine Learning Software Engineer
- Machine Learning Engineer Biotech
- Work From Home Data Engineer
- Full Time Machine Learning Engineer New Grad
- Senior Machine Learning Engineer
- Google Cloud Machine Learning Engineer
What job categories do people searching Pytorch jobs in Dallas, TX look for?
The top searched job categories for Pytorch jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Pytorch jobs?
Cities near Dallas, TX with the most Pytorch job openings:

Full-time, Contractor
Medical, Dental, Vision, Retirement, PTO
Re-posted 25 days ago
Job description
Role Summary:
We are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.
Technical Stack:
LLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.
Frameworks: LangChain, LlamaIndex, and Hugging Face.
Orchestration: LangGraph and Multi-Agent Systems (MAS).
Development: Python, FastAPI, and Asynchronous Programming.
RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.
ML/DL: PyTorch, TensorFlow, and Model Fine-tuning.
Deployment: Docker, Production API management, and LLM monitoring.
Tools: Prompt Engineering, Workflow Design, and GenAI Optimization.
Key Responsibilities:
Develop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.
Build and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.
Integrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.
Design and deploy high-performance, scalable backend services using FastAPI and Async Python.
Fine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.
Optimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.
Containerize and deploy AI services via Docker to production environments.
Required Qualifications:
9+ years of experience ; Hands-on experience building and deploying GenAI applications in a production setting.
Strong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).
Experience with vector search, embedding models, and advanced data retrieval patterns.
Knowledge of model fine-tuning techniques and local LLM quantization/hosting.
Familiarity with production-grade monitoring, API security, and CI/CD for ML.
Compensation, Benefits and Duration
Minimum Compensation: USD 68,000
Maximum Compensation: USD 240,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
About Photon
Sourced by ZipRecruiter
Company size
1 - 10 Employees
Headquarters location
Cambridge, MA, US
Year founded
1984