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Manager Remote Machine Learning Engineer Jobs in Tennessee

... machine learning use cases. Ad-hoc analysis and reporting will remain a core responsibility of this role as the analytics function matures. You'll work closely with a Senior Solutions Engineer who ...

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

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Manager Remote Machine Learning Engineer information

What is a Manager Remote Machine Learning Engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

What is the difference between Manager Remote Machine Learning Engineer vs Data Scientist?

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

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

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

How does a Manager Remote Machine Learning Engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.
What are the most commonly searched types of Remote Machine Learning Engineer jobs in Tennessee? The most popular types of Remote Machine Learning Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Manager Remote Machine Learning Engineer jobs? Cities in Tennessee with the most Manager Remote Machine Learning Engineer job openings:
Analytics Engineer

Analytics Engineer

Esperta Health

Nashville, TN • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago


Job description

Analytics Engineer RemoteFinanceFull time Nashville, Tennessee, United States Overview Application Description Role Overview We are hiring a United States based Analytics Engineer to support reporting, ad-hoc analysis, and analytics development across the organization while helping evolve our data platform over time. This role sits between data engineering and the business. You’ll own day-to-day analytics needs—Power BI dashboards, ad-hoc reporting, SQL development—while growing into more advanced responsibilities such as gold-layer data modeling and, eventually, advanced analytics and machine learning use cases.

Ad-hoc analysis and reporting will remain a core responsibility of this role as the analytics function matures. You’ll work closely with a Senior Solutions Engineer who focuses on data ingestion and integrations, allowing you to focus on transforming data into insight and impact. Why This Role Matters This role is central to how data is used across the company.

You’ll enable faster decision-making today while helping build a more scalable analytics foundation for the future. You’ll have visibility, ownership, and a clear growth path as our data capabilities mature. What You’ll Do Reporting & Ad-Hoc Analytics Own ad-hoc reporting and analysis for operations, finance, and leadership Build and maintain Power BI dashboards and reports Translate ambiguous business questions into clear analytical outputs Partner with stakeholders to define and refine KPIs and metrics Ensure reporting is accurate, performant, and trusted SQL & Data Modeling Write high-quality SQL to support reporting and analytics Build and improve analytics-ready (gold-layer) datasets Contribute to dimensional and fact-based data models Help improve consistency, usability, and documentation of core datasets Growth & Technical Evolution Gradually take on more responsibility in data modeling and analytics engineering Collaborate on improving analytics architecture and best practices Explore advanced analytics or ML use cases over time (as interest and readiness allow) Requirements What We’re Looking For Required Strong expertise in SQL development with a knack for modular design Proven ability working with large and complex datasets Hands on experience building reports or dashboards (Power BI preferred) Experience handling ad-hoc analysis and evolving business questions Experience and understanding of dimensional modeling Ability to communicate clearly with non-technical stakeholders Curiosity and motivation to grow technically Nice to Have 2+ years of SQL development experience Experience with Databricks, Snowflake, or other cloud-based data platforms Familiarity with analytics engineering concepts Familiarity with version control & CI/CD tools (GitHub, Gitlab, etc.) Exposure to healthcare, EMR, or regulated data environments Interest in machine learning or advanced analytics (not required) Benefits Bonus Eligible Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k) Life Insurance Paid Time Off Short Term & Long Term Disability Training & Development