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Manager Learning Solutions Jobs in Tennessee (NOW HIRING)

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Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace. * Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace. * Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Pwc

AI Solutions Engineering Delivery Lead

Nashville, TN · On-site

$99K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... and managing AI and machine learning solutions, particularly with orchestrated LLM applications - Proven specialization in Python, Pandas, Scikit-learn, PyTorch, Langchain, Semantic Kernel, SQL ...

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Showing results 21-40

All JobsLearning Solutions JobsManager Learning Solutions JobsManager Learning Solutions Jobs in Tennessee

Manager Learning Solutions information

See Tennessee salary details

$28.1K

$70.2K

$118K

How much do manager learning solutions jobs pay per year?

As of Aug 13, 2026, the average yearly pay for manager learning solutions in Tennessee is $70,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,500.00 and $79,400.00 per year, depending on experience, location, and employer.

How does a Manager Learning Solutions typically collaborate with subject matter experts and stakeholders when developing training programs?

Managers in Learning Solutions frequently work closely with subject matter experts (SMEs) and stakeholders throughout the design and implementation of training programs. This typically involves conducting needs assessments with stakeholders, facilitating workshops or interviews with SMEs to gather content, and iteratively reviewing training materials to ensure accuracy and alignment with business objectives. Effective collaboration is essential for creating relevant and impactful learning solutions, so strong communication and project management skills are vital. Additionally, Managers often serve as a bridge between technical experts and end-users, translating complex information into engaging, accessible training content.

What does a Manager Learning Solutions do?

A Manager Learning Solutions is responsible for designing, implementing, and overseeing training programs that help employees develop new skills and improve performance. They work closely with stakeholders to assess organizational learning needs, select appropriate instructional methods, and measure the effectiveness of training initiatives. This role often involves managing a team of instructional designers, trainers, or e-learning specialists, as well as coordinating with external vendors. Ultimately, a Manager Learning Solutions ensures that learning strategies align with business goals and support overall organizational growth.

What are the key skills and qualifications needed to thrive as a Manager Learning Solutions, and why are they important?

To thrive as a Manager Learning Solutions, you need expertise in instructional design, adult learning theory, project management, and usually a degree in education, HR, or a related field. Familiarity with Learning Management Systems (LMS), e-learning authoring tools, and relevant certifications like CPLP or ATD are commonly required. Outstanding communication, leadership, and stakeholder management skills help you collaborate effectively and drive organizational learning initiatives. These skills and qualities ensure the development and delivery of impactful learning programs that align with business goals and foster employee growth.

What is the difference between Manager Learning Solutions vs Learning and Development Manager?

AspectManager Learning SolutionsLearning and Development Manager
Primary FocusDesigning and implementing learning technology and solutionsOverseeing overall employee training and development programs
Required CredentialsOften requires certifications in e-learning, instructional design, or related tech skillsTypically requires HR or training certifications, such as CPLP or SHRM-CP
Work EnvironmentTech-driven, project-based, often in corporate or educational settingsHR departments, corporate offices, or training centers
Employer & Industry UsageCommon in tech, corporate, and educational sectorsWidely used across industries with a focus on employee development

While both roles focus on learning and development, the Manager Learning Solutions specializes in creating and managing learning technology and solutions, whereas the Learning and Development Manager oversees broader employee training programs. The choice depends on whether the focus is on tech-based learning or overall employee development.

What are popular job titles related to Manager Learning Solutions jobs in Tennessee?

For Manager Learning Solutions jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Manager Learning Solutions jobs in Tennessee look for?

The top searched job categories for Manager Learning Solutions jobs in Tennessee are:

Manager Learning Solutions jobs near you
Infographic showing various Manager Learning Solutions job openings in Tennessee as of August 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $70,231 per year, or $33.8 per hour.

Principal Machine Learning Engineer

Ll Oefentherapie

Nashville, TN • On-site

$126 - $150/hr

Other

Posted 4 days ago

Job description

Hot Job

  • Job Identification 340943
  • Job Category Product and Research
  • Posting Date 07/23/2026, 11:30 PM
  • Job Type Regular Employee
  • Does this position require a security clearance? No
  • Years 6 to 10+ years
  • Applicants are required to read, write, and speak the following languages English
Job Description

Implements machine learning (ML) models for production. Ensures the readiness of machine learning models for deployment in production. Automates machine learning workflows. Creates infrastructure and frameworks to monitor the performance of machine learning models in deployment. Evaluates potential data quality, security, and/or privacy issues and their impacts on modeling. Provides troubleshooting and debugging support. Addresses issues in machine learning infrastructure and workflows. Collaborates with stakeholders to integrate machine learning models into new or extant systems. Develops, maintains, and refines tools, platforms, and services for internal use. Develops efficient, bug-free code from scratch. Maintains familiarity with current developments in the machine learning field and integrates knowledge into model development.

Responsibilities

KeyResponsibilities

MachineLearning and Data Modeling – Model Productionization:

  • Utilizesmachine learning (ML) and software development knowledge to implement ML modelsfor production.
  • Engagesin transforming machine learning prototypes into production-ready models.
  • Collaborateswith multiple stakeholders, such as Development Leads, Product Management,Operations, and Release Management, to make, adopt, and communicate technicaldecisions, and shape the development and delivery of software.

ModelDevelopment and Deployment – Model Deployment:

  • EnsuresML model readiness for deployment by scaling models, cleaning model code, andensuring production quality standards are met.
  • Automatesmachine learning workflows, from data extraction, transformation, and loading(ETL) to model deployment and monitoring, to establish the continuousintegration and continuous delivery of machine learning solutions.

ModelDevelopment and Deployment – Model Performance:

  • Createsinfrastructure and frameworks to monitor the performance and alignment withdesign criteria of trained models and/or systems.
  • Proactivelymonitors the performance of deployed models and troubleshoots independently orin collaboration with Data Science.
  • Developsnovel metrics that provide analytical insights to non-technical stakeholders onhow well machine learning models are operating.

ModelDevelopment and Deployment – Data Quality:

  • Evaluatespotential issues related to data quality (e.g., bias, fairness), data security,and data privacy, and minimizes their impacts on data analyses and modeling.
  • Engagesin tasks such as data cleaning, preprocessing, and feature identification toprepare for and enable model training.

InternalCollaborations and Impacts – Model Integration and Operation:

  • Collaborateswith multiple stakeholders (e.g., data scientists, software developers) tointegrate ML models into new or existing systems.
  • Maintainsthe partnership between model development and operations, ensuring smoothdeployment and continuous improvement of ML models.
  • Understandssoperational considerations of model deployment (e.g., performance, scalability,stability, maintenance).
  • Providesexpert troubleshooting and debugging support, addresses issues in machinelearning infrastructure and workflow, and creates robust solutions to preventfuture problems.

InternalCollaborations and Impacts – Tool Development:

  • Develops,maintains, and refines tools, platforms, environments, and services forinternal use.

InternalCollaborations and Impacts – Coding and Documentation:

  • Developsefficient, bug-free, medium-complexity code from scratch, and properlymaintains and organizes the existing codebase.
  • Implementsbest practices for version control, code review, and code delivery/deployment.
  • Buildsand maintains professional documentation for technical processes(experimentation, data collection and analyses, model building).
  • Testsand reviews code for bugs.

MachineLearning Expertise:

  • Maintainsfamiliarity with current developments in the machine learning field andintegrates knowledge into model development.
  • Maintainsfamiliarity with the usage and development of third-party machine learningframeworks, packages, and libraries (e.g., PyTorch, TensorFlow, Keras) tocontinuously evaluate their performance and scalability, and integrate theminto production environments.

CoreResponsibilities

Planning& Execution:

  • Managesand coordinates moderately complex tasks, monitoring timelines and deliverablesto ensure timely completion and adherence to requirements for a moderatelysized project or initiative.
  • Efficientlydelegates, monitors, and prioritizes work across multiple projects, providingtechnical oversight and adjusting plans to address shifts in resources ortimelines.
  • Collaboratesacross the organization to align on expectations and achieve shared objectives.
  • Leveragesunderstanding of business leaders, stakeholders, and/or customers to ensureproposed solutions meet their needs.
  • Supportsinclusivity by actively seeking and listening to diverse perspectives, ensuringothers feel heard and respected.

ProblemSolving:

  • Identifiesand addresses moderately complex issues by analyzing a wide range of dataand/or information to identify solutions in accordance with standard practices.
  • Proactivelyescalates unresolved or critical issues with a thorough assessment and suggestspotential solutions.
  • Reviews,contributes to, and documents problem solving strategies.
  • Pursueslearning opportunities to expand knowledge and skills and/or tools in new areasand stays abreast of the latest industry trends and best practices.
  • Proactivelyseeks and leverages ongoing feedback and training to improve skills.
  • Coachesand mentors junior team members, fostering continuous learning and knowledgesharing within and across teams.
  • Developsideas, recommends updates, and/or collaborates on the implementation of processimprovements to increase the efficiency and effectiveness of processes,protocols, and workflows across teams, and evaluates the impact on keystakeholders.
  • Solicitsfeedback from others on ideas for alternative approaches and methods forcontinued improvement.

Performanceand Development:

  • Contributesto the talent development pipeline by participating in candidate interviews,assessing candidates, and providing hiring recommendations.
Qualifications

Disclaimer:

Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $126,200 to

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