1

Pytorch Developer Jobs in Dallas, TX (NOW HIRING)

Engineer

Irving, TX · On-site

$95K - $105K/yr

... Engineering, RAG Architecture, Agentic AI. - Basic knowledge of Hybrid prompting technique ... PyTorch, TensorFlow, Keras - Hands-On knowledge on NLP - Understanding of model deployment and ...

The Gen AI-ML Engineer is an intermediate level position responsible for participation in the ... TensorFlow, PyTorch * LLMs: Llama, Gemini, GPT-4, and other advanced LLMs. * Vector Databases:

Engineer

Irving, TX · On-site

$90K - $100K/yr

... Engineering, RAG Architecture, Agentic AI. - Basic knowledge of Hybrid prompting technique ... PyTorch, TensorFlow, Keras - Hands-On knowledge on NLP - Understanding of model deployment and ...

Python Developer with ML - Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

... PyTorch, TensorFlow). • Architect modular, scalable, and extensible frameworks for APIs, data processing, or AI integrations. • Implement best practices in software engineering: OOP, design ...

Python Developer with ML - Dallas, TX

Dallas, TX · On-site

$50 - $68.75/hr

... PyTorch, TensorFlow). • Architect modular, scalable, and extensible frameworks for APIs, data processing, or AI integrations. • Implement best practices in software engineering: OOP, design ...

next page

Showing results 1-20

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 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 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 cities near Dallas, TX are hiring for Pytorch Developer jobs? Cities near Dallas, TX with the most Pytorch Developer job openings:
US_East | Software Developer - Testing Tools/Automation/Performance _L2

US_East | Software Developer - Testing Tools/Automation/Performance _L2

Redolent, Inc.

Plano, TX • On-site

Contractor

Posted 25 days ago


Job description

Description:
"Possible 3 Month CTH | No Fees | Do Not Re-Post| Confidential
TMR ID: YWTWG2
Role: V&V Engineer - AI-Driven Testing & Validation
Work location: Plano, TX
Background and Meet and Greet: MANDATORY
Job Description:
"Key Responsibilities
AI/ML & LLM Development/Validation
Lead end-to-end quality engineering for enterprise AI applications, including LLM-powered products, RAG pipelines, and agentic workflows.
Design and execute prompt validation strategies, evaluating LLM responses for accuracy, semantic relevance, hallucination risk, and safety compliance.
Build automated evaluation pipelines for AI model outputs using metrics such as BLEU, ROUGE, embedding-based similarity, precision, recall, and F1-score.
Validate agentic systems (tool use, multi-step reasoning, planner-executor workflows) for correctness, determinism, and failure mode handling.
Test Automation & Frameworks
Architect and maintain Python-based automation frameworks for AI/ML model evaluation, regression testing, and continuous model quality monitoring.
Integrate AI testing into CI/CD pipelines, enabling automated evaluation of model updates, prompt changes, and dataset revisions before release.
Develop reusable test harnesses for prompt regression, golden-set evaluation, A/B comparison of model versions, and human-in-the-loop review workflows.
Data Quality, Bias & Fairness
Perform AI data validation across training and inference pipelines using exploratory data analysis (EDA), schema validation, and cross-validation techniques.
Conduct bias detection and fairness analysis across demographic and contextual slices to ensure responsible AI outcomes.
Drive model robustness testing, including adversarial inputs, distribution shift detection, and stress testing under edge cases.
Establish regression testing standards for retraining and fine-tuning cycles to prevent quality drift after model updates.
Collaboration & Leadership
Partner with client AI engineers to validate solutions built using TensorFlow, PyTorch, LangChain, LangGraph, and LlamaIndex.
Define quality KPIs and acceptance criteria for AI features, and report quality posture to engineering and product leadership.
Mentor QA engineers on AI evaluation methodologies, ML fundamentals, and modern test automation practices.
Champion responsible AI practices, including safety, transparency, explainability, and compliance with evolving AI governance standards.
Required Qualifications
10+ years of professional experience in Quality Engineering and Test Automation, validating complex enterprise applications.
Proficient in validating AI/ML systems, including Generative AI and LLM-based applications.
Strong proficiency in Python and experience building automation frameworks from the ground up.
Practical experience with prompt validation, agentic workflow testing, and AI model evaluation.
Working knowledge of evaluation metrics: BLEU, ROUGE, embedding similarity, precision, recall, F1-score, and human-evaluation methodologies.
Experience with AI/ML frameworks and ecosystems: TensorFlow, PyTorch, LangChain, LangGraph, and LlamaIndex.
Solid understanding of data validation techniques: EDA, schema validation, cross-validation, and statistical analysis.
Experience integrating automated testing into CI/CD pipelines (e.g., GitHub Actions, Jenkins, GitLab CI, Azure DevOps).
Familiarity with bias detection, fairness assessment, and AI safety evaluation techniques.
Preferred Qualifications
Experience with vector databases, retrieval-augmented generation (RAG), and embedding pipelines.
Background in MLOps tooling such as MLflow, Weights & Biases, or similar experiment tracking platforms.
Exposure to LLM observability and evaluation tools (e.g., LangSmith, Ragas, DeepEval, TruLens).
Familiarity with cloud AI services on AWS, Azure, or GCP (Bedrock, Azure OpenAI, Vertex AI).
Knowledge of AI governance frameworks, model cards, and emerging AI regulatory standards.
Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field."
The following details must accompany your submission:
First Name, Middle name, and Last Name:
City and State:
Open to Relocate?
Rate:
Availability:
Phone #:
Mobile #:
Email address:
Visa type:
Visa Expiration Date:
Hiring Status:
MiguelAngel Buonafina - ERM
Capgemini North America
Tel.: +1 888-229-2961"
Additional Details
  • Global Grade : B
  • Named Job Posting? (if Yes - needs to be approved by SCSC) : No
  • Remote work possibility : No
  • Global Role Family : 60236 (P) Software Engineering
  • Global Technical Skills Family : 6249 (T) Testing Tools / Testing Automation / Performance Testing Tools
  • Local Role Name : V&V Engineer - AI-Driven Testing & Validation
  • Local Skills : Julie Skidmore
  • Languages Required: : English

Redolent logo

About Redolent

Sourced by ZipRecruiter

Redolent, a dynamic and rapidly expanding company committed to excellence in software solutions, where success is fueled by a combination of technical expertise and efficient management practices. Our solutions create a measurable delta in our clients’ productivity and profitability, contributing to their growth and success.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

San Jose, CA, US

Year founded

2008

Social media