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Tensorflow Pytorch Jobs in Tennessee (NOW HIRING)

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Design and implement machine learning models using frameworks such as PyTorch, TensorFlow, or equivalent * Formulate and solve optimization problems using ML techniques * Pathfinding and routing

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Design and implement machine learning models using frameworks such as PyTorch, TensorFlow, or equivalent * Formulate and solve optimization problems using ML techniques * Pathfinding and routing

Active certification or advanced certification in Python, Pyspark, Pytorch, and Tensorflow. * Ability to travel 20%, on average, based on the work you do and the clients and industries/sectors you ...

Proficiency in Python (PyTorch, TensorFlow, HuggingFace), and familiarity with MLOps frameworks like MLflow or Kubeflow * Cloud experience with AWS/GCP/Azure; containerization with Docker/Kubernetes ...

Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience translating research ideas into production systems. Preferred Qualifications: * Deep experience with ...

Showing results 41-60

Tensorflow Pytorch information

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.
What are popular job titles related to Tensorflow Pytorch jobs in Tennessee? For Tensorflow Pytorch jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Tensorflow Pytorch jobs? Cities in Tennessee with the most Tensorflow Pytorch job openings:

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

Starbucks

Nashville, TN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago


Starbucks rating

6.7

Company rating: 6.7 out of 10

Based on 3,615 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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