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Python Ml Developer Jobs in Tennessee (NOW HIRING)

OneOncology

Sr. AI Software Engineer

Nashville, TN · On-site

$118.30K - $156K/yr

Expert Python; strong foundations in distributed systems, data engineering, and software design * Required experience with Azure and Databricks (Azure ML, Databricks workflows, MLflow, Spark ...

Octave

Sr. Data Engineer

Nashville, TN

$110.60K - $132.80K/yr

Develop foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) ... Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN · On-site

$118.30K - $156K/yr

... Python-based ML components that work seamlessly with existing product platforms across multiple ... engineers and contribute to team knowledge-sharing around ML best practices, tooling, and ...

Deloitte

Manager, GenAI Engineering

Hermitage, TN · On-site

Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc. • Strong understanding and ... , ADO, GitHub, SonarQube, etc. to deliver high quality products rapidly. • Excellent ...

Spectra Tech, Inc.

I&C Engineer

Oak Ridge, TN

$72.40K - $93.70K/yr

Oversee engineering automation via Python, MATLAB, or advanced Excel; review and validate automated outputs. * Champion responsible integration of AI/ML into controls systems, including predictive ...

FOCUSPOINT

AI Engineer

Nashville, TN · On-site

AI Engineer Location: Varies by client Employment Type: Contract Pay: Commensurate with experience ... AI/ML development, with hands-on work deploying models in production * Proficiency in Python ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100.90K - $138.60K/yr

Experience building and maintaining end-to-end ML pipelines * Strong programming skills in Python (additional languages are a plus) * Experience working with real-world, imperfect datasets * Ability ...

SPECTRA TECH INC

I&C Engineer

Oak Ridge, TN

$72.40K - $93.70K/yr

Oversee engineering automation via Python, MATLAB, or advanced Excel; review and validate automated outputs. Champion responsible integration of AI/ML into controls systems, including predictive ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100.90K - $138.60K/yr

Experience building and maintaining end-to-end ML pipelines * Strong programming skills in Python (additional languages are a plus) * Experience working with real-world, imperfect datasets * Ability ...

SPECTRA TECH, Inc.

I&C Engineer

Oak Ridge, TN · On-site

$72.40K - $93.70K/yr

Leadership in Automation & AI/ML • Direct process-improvement initiatives: automate calculations ... via Python, MATLAB, or advanced Excel; review and validate automated outputs. • Champion ...

ITR

Full Stack Developer

Oak Ridge, TN

Python * MCP (Model Context Protocol or similar frameworks) * Experience working with Agentic AI ... Experience integrating AI/ML models into production applications * Strong understanding of UI/UX ...

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Python Ml Developer information

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What are popular job titles related to Python Ml Developer jobs in Tennessee? For Python Ml Developer jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Tennessee look for? The top searched job categories for Python Ml Developer jobs in Tennessee are:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Tennessee as of May 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, 2% Contract, and 2% Nights. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.
Sr. AI Software Engineer

Sr. AI Software Engineer

OneOncology

Nashville, TN • On-site

$118.30K - $156K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

OneOncology rating

7.7

Company rating: 7.7 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

Job description

OneOncology is positioning community oncologists to drive the future of medical care through a patient-centric, physician-driven, and technology-powered model to help improve the lives of everyone living with cancer and other diseases. Our team is bringing together leaders to the market place to help drive OneOncology's mission and vision.
Why join us? This is an exciting time to join OneOncology. Our values-driven culture reflects our startup enthusiasm supported by industry leaders in oncology, urology, technology, and finance. We are looking for talented and highly-motivated individuals who demonstrate a natural desire to improve and build new processes that support the meaningful work of independent physicians and the patients they serve.
Job Description:
We are seeking a Senior AI Engineer to lead the design, development, and production deployment of advanced AI systems on Azure and Databricks, reporting to the Manager, Software Engineering & AI. You will own the technical direction for agentic AI platforms, Retrieval Augmented Generation (RAG) architectures, and large-scale model training and serving across the organization. This is a senior individual-contributor role with significant architectural authority: you will set standards, mentor engineers, partner closely with product and clinical stakeholders, and be accountable for the reliability, cost, and clinical safety of the AI systems you deliver. Success in this role requires deep machine learning expertise, proven production experience on Azure and Databricks, and strong judgment to make sound trade-offs in a regulated healthcare environment.
Responsibilities:
  • Architect and lead end-to-end agentic AI systems enabling autonomous decision-making, multi-step planning, and tool use; design planning, reasoning, memory, and orchestration layers with strong evaluation, observability, and guardrails

  • Drive performance, safety, and cost optimization for agents operating in complex, dynamic environments

  • Own production RAG architecture across structured and unstructured oncology data; optimize for retrieval quality, latency, and grounding

  • Design scalable indexing, hybrid retrieval strategies, and evaluation frameworks; lead fine-tuning, adapters, and prompt engineering to improve LLM performance

  • Lead training and deployment of LLMs and deep learning models on Azure ML and Databricks, including distributed GPU training

  • Define scalable data preprocessing, feature engineering, and labeling pipelines; drive optimization across hyperparameters, architecture, quantization, and serving

  • Own full model lifecycle: versioning, evaluation, monitoring, drift detection, and retraining

  • Set technical direction for AI workloads across Azure and Databricks; design secure, scalable, HIPAA-compliant data and ML pipelines

  • Establish standards for cost, performance, reliability, and capacity planning, including FinOps for AI infrastructure

  • Define and enforce MLOps practices including CI/CD, automated evaluation, A/B testing, canary deployments, and incident response

  • Build reusable platform tooling to accelerate safe and efficient AI feature delivery

  • Mentor engineers, lead design reviews, and elevate code quality and evaluation rigor

  • Collaborate cross-functionally to deliver AI solutions aligned with clinical and business outcomes

  • Translate ambiguity into clear technical roadmaps and communicate trade-offs to executive, technical, and clinical stakeholders

  • Shape organizational AI strategy, standards, and responsible AI practices

  • Evaluate emerging models and techniques, driving adoption where valuable

  • Represent the organization in industry forums, conferences, and partner engagements

  • Additional responsibilities as assigned to help drive our mission of improving the lives of everyone living with cancer.

Required or Preferred Qualifications (specify within):
  • Bachelor's or Master's in Computer Science, AI, or related field (or equivalent experience)

  • 7+ years software/ML engineering, including 3+ years building and operating production ML/LLM systems

  • Proven track record delivering AI/ML systems from prototype to scaled production

  • Deep expertise in LLMs, transformers, fine-tuning, and inference optimization

  • Expert Python; strong foundations in distributed systems, data engineering, and software design

  • Required experience with Azure and Databricks (Azure ML, Databricks workflows, MLflow, Spark pipelines)

  • Hands-on experience with vector databases (e.g., Azure AI Search, Databricks Vector Search, pgvector, FAISS) and RAG patterns

  • Experience with LLM orchestration and agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)

  • Strong evaluation practices (offline/online evals, golden datasets, quality metrics for LLM/agent systems)

  • Excellent problem-solving, communication, and cross-functional collaboration skills

Preferred:
  • Experience designing and shipping agentic AI systems in production.

  • Experience implementing RAG over regulated or sensitive data (healthcare, finance, legal).

  • Experience with MLOps tooling and platform engineering for AI (model registries, feature stores, serving infrastructure, observability).

  • Experience with healthcare data standards (FHIR, HL7) and operating within HIPAA-compliant environments.

  • Experience mentoring engineers and leading technical initiatives across teams.

  • Contributions to open-source AI projects, publications, or patents.

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