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Pytorch Developer Jobs in Tennessee (NOW HIRING)

Elevance Health

Gen AI Engineer

Nashville, TN · Hybrid

Gen AI Engineer Gen AI Engineer Location: This role requires associates to be in-office 1 - 2 days ... TensorFlow, Keras, PyTorch, and Spark. * Experience with GCP/AWS cloud platforms. * Strong ...

Elevance Health

Gen AI Engineer

Nashville, TN · Hybrid

Gen AI Engineer Location: This role requires associates to be in-office 1 - 2 days per week ... TensorFlow, Keras, PyTorch, and Spark. * Experience with GCP/AWS cloud platforms. * Strong ...

Cisco

Applied AI Scientist

Memphis, TN · On-site

Collaborate with engineering, product, and data science teams to understand requirements ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Cisco

Applied AI Scientist

Nashville, TN

Collaborate with engineering, product, and data science teams to understand requirements ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Oracle

Senior Principal Software Engineer

Nashville, TN · On-site

$121K - $167K/yr

Familiarity with AI/ML frameworks (Tensorflow/Keras, PyTorch, Scikit-Learn, XGBoost, Caffe) as well ... Responsibilities As a member of the software engineering division, you will take an active role in ...

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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 Tennessee?

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

What job categories do people searching Pytorch Developer jobs in Tennessee look for?

The top searched job categories for Pytorch Developer jobs in Tennessee are:

What cities in Tennessee are hiring for Pytorch Developer jobs?

Cities in Tennessee with the most Pytorch Developer job openings:

Pytorch Developer jobs near you

principal engineer-AI Sourcing & Procurement (Nashville, TN)

Starbucks

Nashville, TN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 days ago

Starbucks rating

6.7

Company rating: 6.7 out of 10

Based on 3,619 frontline employees who took The Breakroom Quiz

3rd of 16 rated cafes

Job description

Now Brewing - Engineering Principal, AI Sourcing & Procurement Platforms (Nashville, TN)
Location: Nashville, TN (Onsite - four days per week)
From the beginning, Starbucks set out to be a different kind of company-one that not only celebrated coffee and its rich tradition, but also built meaningful connections. We are known for developing extraordinary leaders who are guided by service to others and driven to make an impact at global scale.
We are seeking a hands-on Engineering leader to head the development of AI-powered sourcing and procurement platforms, modernizing how Starbucks plans, sources, negotiates, and executes across a complex global supply chain. This leader will build and scale secure, reliable, and high-velocity AI systems that directly impact cost, availability, and operational resilience.
This role is based in Nashville and sits at the intersection of AI engineering, enterprise platforms, and real-world business execution, with an expectation of rapid iteration, strong technical rigor, and close partnership with procurement, supply chain, and business teams
Summary of Key Responsibilities
Technical Strategy & Thought leadership:
  • Define and drive the technology vision and roadmap for AI-enabled sourcing and procurement platforms, balancing speed, scalability, security, and reliability.
  • Partner closely with procurement, supply chain, finance, product, and data science teams to translate business needs into AI-driven capabilities (e.g., sourcing optimization, supplier intelligence, contract insights).
  • Own architectural decisions for LLM-powered and agentic systems, ensuring platforms evolve safely and predictably as models, tools, and use cases change.
  • Operate effectively in a dynamic, fast-moving environment, with wicked-fast deployment cycles and a bias toward responsible delivery over perfection.

Team Leadership and Management:
  • Lead and mentor a team of platform, infrastructure, and AI engineers, fostering a culture of ownership, learning, and execution.
  • Set clear technical standards and expectations while empowering engineers to move quickly and safely.
  • Coach partners through ambiguity, trade-offs, and real-world constraints common in applied enterprise AI.
  • Like all good AI roles, this one is a hands on and requires servant leadership in demonstrating what good looks like.

Engineering Management:
Infrastructure & Operational Excellence
  • Enable high developer productivity through CI/CD, infrastructure-as-code, Kubernetes, and automated testing, with a strong emphasis on deployment speed and reliability.
  • Establish and use operational metrics (DORA metrics, SLOs, SLIs, error budgets) to balance innovation with stability.
  • Implement best-in-class monitoring, logging, and alerting to ensure platform health and rapid incident response.
  • Lead thoughtful decisions around model tradeoffs, token usage, cost optimization, and performance in production AI systems .

Applied AI: Rigor, Safety & Trust
  • Ensure back testing, AI evaluations, and performance benchmarking are integral to model and agent development-not optional afterthoughts.
  • Embed AI security, data protection, and access controls by design, partnering closely with Security and Architecture teams.
  • Drive disciplined practices around prompt management, model versioning, regression testing, and controlled rollout of AI capabilities.
  • Ensure AI systems are explainable, auditable, and appropriate for enterprise sourcing and procurement use cases.

Technical Environment & Tooling
  • Hands-on familiarity with modern AI development tools, including GitHub Copilot, Cursor, and similar AI-assisted engineering tools, and an expectation to model their effective use.
  • Build and operate systems leveraging LLMs, agentic orchestration, and intelligent workflows aligned to real business outcomes.
  • Collaborate across data platforms and enterprise systems supporting procurement and supply chain operations.

Basic Qualifications:
  • Bachelor's degree in computer science or information systems or equivalent experience.
  • Minimum 10 years of technology related work experience
  • Minimum 2 years leveraging LLMs in development
  • Must love to code and work through engineering challenges using GenAI

Experience required:
  • 8+ years of building scalable services on top of public cloud infrastructure, preferably Azure and AWS
  • 8+ years' experience designing, building and operating large-scale distributed systems and infrastructure
  • 5+ years' experience with data and AI platforms (e.g. Databricks, Azure)
  • Deep knowledge of containerization & orchestration (Kubernetes, Docker), IaC and CI/CD technologies.
  • Experience working with AI and Machine Learning frameworks (e.g. LangChain, LangGraph, Semantic Kernel, TensorFlow, PyTorch), and APIs
  • Proficiency with at +1 scripting language (e.g. Python, Powershell, Go)
  • Proficiency in RAG pipelines, experience with multi-agent orchestration (MCP, A2A, etc), and skill/tool use is critical.
  • Ability to identify, analyze and resolve complex technical issues, ensuring optimal performance, scalability and user experience.
  • Strong communication and collaboration skills with cross-functional partners, including those with and without technical backgrounds.
  • Demonstrated willingness to learn continuously, adopt new technologies and approaches, and share knowledge within the technical
    community.
  • Growth-minded, solution-oriented approach with a proven track record of driving projects from concept to impact.
  • Experience in managing geographically distributed teams.

As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor's degree through Arizona State University's online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com .
*If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.

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