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Pytorch Developer Jobs in Frisco, TX (NOW HIRING)

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit ... GCP Professional Machine Learning Engineer certification is required. Experience with version ...

NTT DATA Services

SAP AI Lead Developer

Plano, TX · On-site +1

$56.50 - $74/hr

... PyTorch, Scikit-learn), and programming languages (Python, R). • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Strong architectural design and system integration skills ...

NTT DATA Services

SAP AI Lead Developer

Plano, TX · On-site

$56.50 - $74/hr

... PyTorch, Scikit-learn), and programming languages (Python, R). • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Strong architectural design and system integration skills ...

NTT DATA Services

SAP AI Lead Developer

Plano, TX · On-site +1

$56.50 - $74/hr

Proficiency with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), and programming languages (Python, R). Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Strong ...

IT America Inc

ML Engineer

Plano, TX · On-site

Develop and optimize machine learning and deep learning models using frameworks like TensorFlow or PyTorch. * Strong skills in programming languages such as Python, R, or Java, essential for ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

... PyTorch, or scikit-learn. • Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. • ...

FedEx Office

Ops Emerging Tech Developer

Plano, TX · Hybrid

The Ops Emerging Technology Developer will research, plan, lead, develop, and implement solutions ... Experience with AI/ML or AIenabled solutions, frameworks, or services (e.g., TensorFlow, PyTorch ...

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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 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.
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Pytorch Developer jobs near you

Senior Machine Learning Engineer (NLP/LLM Focus)

CALL BOX

Dallas, TX • On-site

$112K - $148K/yr

Other

Medical, Dental, Life, Retirement

This job post has expired today. Applications are no longer accepted.

Job description

Description

 At Call Box, we believe in fostering growth-both personal and professional. We hire smart, ambitious individuals who are passionate about technology and empower them to push the boundaries of what's possible. We build and deploy AI-driven solutions that leverage cutting-edge Natural Language Processing (NLP) and Large Language Models (LLMs) to solve complex business problems in real-world environments. 


As a Senior Machine Learning Engineer specializing in NLP and LLM-powered models and microservices, you'll play a key role in shaping and delivering ML-powered products that transform how we process and extract insights from unstructured data. You'll focus on deploying scalable, high-impact solutions, with an emphasis on productization rather than research. If you're passionate about using advanced NLP techniques to solve real-world problems and have a knack for deploying and maintaining models at scale, this is the role for you. 


We use a wide range of tools including Python, TensorFlow, PyTorch, Hugging Face, SQL, Kubernetes, Docker, Azure, and AWS. Candidates with experience in data engineering or MLOps (e.g., MLflow, CDK/terraform) are highly preferred. 

Requirements

 What You'll Do: 

- Lead the design, development, and deployment of NLP and LLM-powered models that drive key products and business functions. 

- Turn cutting-edge models into production-ready, scalable solutions, ensuring seamless integration into our applications. 

- Build APIs and pipelines that power AI-driven insights from a variety of data sources like call transcriptions and enable our products to understand and process natural language data, including text classification, conversational AI, and document analysis. 

- Collaborate with product teams, engineers, and other stakeholders to drive the vision and execution of ML-powered solutions. 

- Ensure MLOps best practices are followed, with a focus on model monitoring, versioning, and retraining workflows. 

- Serve as a technical mentor through code reviews, pair programming, and guidance on best practices. 

What You Need: 

- A relentless passion for learning, growth, and excellence in the field of machine learning. 

- 5+ years of experience in machine learning engineering with a focus on NLP and LLM technologies (e.g., BERT, GPT, or similar transformer models). 

- Proven experience in building and deploying large-scale NLP models for real-world applications. 

- Expertise in turning research-based models into scalable, production-level solutions. 

- Strong programming skills in Python, with deep familiarity in libraries like TensorFlow, PyTorch, or Hugging Face. 

- Experience with cloud-based infrastructures (AWS, Azure, GCP) and tools like Kubernetes, Docker, and MLflow. 

- A team-oriented mindset, with a passion for collaborating and mentoring others. 

Preferred Skills: 

- Hands-on experience with data engineering tasks such as data pipelines, ETL processes, and working with big data technologies like Spark. 

- Familiarity with MLOps tools and practices, including continuous integration/deployment pipelines for machine learning applications. 

- Expertise in automation of model retraining and ensuring long-term scalability and performance of deployed models. 

- Experience with the automotive sales industry, voice recognition, or call center technologies. 

What's In It for You: 

- Competitive salary ranging from based on experience. 

- Medical and dental insurance options. 

- Company provided Long Term Disability and Life Insurance. 

- 401k with company match to help secure your financial future. 

- A monthly wellness allowance, reading stipend, and other perks to ensure a healthy work-life balance. 

- Clear opportunities for career growth with mentorship from senior leaders. 

- An exciting, collaborative work environment with regular team-building activities, and company events. 

Apply