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Volunteer Mlops Engineer Jobs (NOW HIRING)

The Campbell's Company

$115K - $138K/yr

Our "Campbell's Cares" program matches employee donations and/or volunteer activity up to $1,500 ... MLOps & CI/CD: Support deployment, testing, and automation for data and AI solutions. * Data ...

Crusoe

Senior Staff Solutions Engineer (NYC)

Denver, CO · On-site

$56.75 - $73.25/hr

Kubernetes + MLOps Focus: Architect and deploy ML workloads using Kubernetes-based stacks (e.g ... Volunteer time off * Global travel insurance & emergency assistance * Daily meals allowance

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for ... for volunteer time each calendar year. To learn more about working at Yum! - Click here. At Yum ...

Yum Brands

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for ... for volunteer time each calendar year. To learn more about working at Yum! - Click here. At Yum ...

ProducePay

Senior Staff Solutions Engineer (NYC)

Denver, CO · On-site

$56.75 - $73.25/hr

Kubernetes + MLOps Focus: Architect and deploy ML workloads using Kubernetes‑based stacks (e.g ... Volunteer time off * Global travel insurance & emergency assistance * Daily meals allowance

Crusoe

Senior Staff Solutions Engineer (NYC)

Denver, CO · On-site

$56.75 - $73.25/hr

Kubernetes + MLOps Focus: Architect and deploy ML workloads using Kubernetes-based stacks (e.g ... Volunteer time off * Global travel insurance & emergency assistance * Daily meals allowance

Amches, Inc.

2906 AI Engineer

Annapolis, MD · On-site

... operations (MLOps) tools for deploying and managing machine learning models at scale. Benefits ... voluntary life insurance available #J-18808-Ljbffr

InterImage

... MLOps) tools for deploying and managing machine learning models at scale. InterImage Benefit ... voluntary life insurance available #CJ Employment Type: FULL_TIME

KFC Corporation

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for ... Floating day off * 2 paid days for volunteer time each calendar year To learn more about working at ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

Goosehead

AI Agent Engineer

Westlake, OH

Implement best practices in MLOps, ensuring reproducibility, observability, and seamless deployment ... High quality voluntary health, vision, disability, life, and dental insurance programs * 401K ...

Talkspace

Senior Data Engineer

New York, NY · On-site

$146K - $180K/yr

MLOps Implementation * Develop and maintain MLOps pipelines that automate the deployment ... HSA/ FSA * 401k Retirement Savings Program with matching up to 4% * Voluntary benefits including ...

InterImage

2906 AI Engineer

Annapolis, MD · On-site

... MLOps) tools for deploying and managing machine learning models at scale. InterImage Benefit ... additional voluntary life insurance available #CJ Clearance Level: TS/SCI FSP Job Location:

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Volunteer Mlops Engineer information

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How much do volunteer mlops engineer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for volunteer mlops engineer in the United States is $19.14, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $20.19 per hour, depending on experience, location, and employer.

What is a volunteer MLOps engineer?

Volunteer MLOps Engineers are professionals who donate their time and expertise to manage and streamline the deployment, monitoring, and maintenance of machine learning models within organizations, typically nonprofits or open-source projects. They work on automating workflows, ensuring scalability, and maintaining the reliability of ML systems without monetary compensation. Their contributions help organizations leverage machine learning technologies efficiently while minimizing operational bottlenecks.

What are the key skills and qualifications needed to thrive as a volunteer MLOps engineer?

To thrive as a Volunteer MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud computing, often supported by experience with data pipelines and deployment processes. Familiarity with tools and platforms such as Docker, Kubernetes, CI/CD pipelines, and cloud services like AWS or GCP is typically required, along with knowledge of version control systems. Strong collaboration, problem-solving skills, and the ability to communicate technical concepts clearly are valuable soft skills in this role. These skills and qualities are crucial for ensuring reliable, scalable, and efficient deployment of machine learning models in collaborative, often resource-constrained environments.

What are some common challenges faced by volunteer MLOps engineers, and how can they be addressed?

Volunteer MLOps Engineers often encounter challenges related to limited resources, such as restricted access to cloud services or hardware, and working with diverse teams who may be spread across different time zones. Effective communication and leveraging open-source tools can help mitigate these issues. Collaborating closely with data scientists and developers, setting clear documentation standards, and prioritizing automation can streamline workflows even in a volunteer setting. Being proactive in seeking feedback and sharing best practices also helps foster a supportive and productive environment.

What is the difference between Volunteer Mlops Engineer vs Data Engineer?

AspectVolunteer Mlops EngineerData Engineer
Required CredentialsBasic understanding of MLOps tools, some experience with cloud platformsStrong SQL, ETL, and database skills, often with certifications in data management
Work EnvironmentNon-profit or open-source projects, remote or flexible settingsCorporate or enterprise data teams, often in office or hybrid setups
Industry UsageAI/ML projects, research, non-profit initiativesData infrastructure, analytics, business intelligence

Volunteer Mlops Engineers focus on deploying and maintaining machine learning models in a volunteer or non-profit context, often with less formal credentials. Data Engineers build and manage data pipelines and infrastructure, typically in corporate environments. While both roles involve working with data and cloud tools, Volunteer Mlops Engineers are more specialized in ML deployment, whereas Data Engineers focus on data architecture and processing.

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Volunteer Mlops Engineer jobs near you
Infographic showing various Volunteer Mlops Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $39,804 per year, or $19.1 per hour.

Engineer II - Machine Learning - PODS

Clearwater, FL • On-site

Polluxa, Inc.
See more jobs at Polluxa, Inc.external

$150 - $200/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

JOB SUMMARY

The Data Engineer- Machine Learning is responsible for scaling a modern data & AI stack to drive revenue growth, improve customer satisfaction, and optimize resource utilization. As an ML Data Engineer, you will bridge data engineering and ML engineering: build high‑quality feature pipelines in Snowflake/Snowpark, Databricks, productionize and operate batch/real‑time inference, and establish MLOps/LLMOps practices so models deliver measurable business impact at scale.

ESSENTIAL DUTIES AND RESPONSIBILITIES
  • Design, build, and operate feature pipelines that transform curated datasets into reusable, governed feature tables in Snowflake
  • Productionize ML models (batch and real‑time) with reliable inference jobs/APIs, SLAs, and observability
  • Setup processes in Databricks and Snowflake/Snowpark to schedule, monitor, and auto‑heal training/inference pipelines
  • Collaborate with our Enterprise Data & Analytics (ED&A) team centered on replicating operational data into Snowflake, enriching it into governed, reusable models/feature tables, and enabling advanced analytics & ML—with Databricks as a core collaboration environment
  • Partner with Data Science to optimize models that grow customer base and revenue, improve CX, and optimize resources
  • Implement MLOps/LLMOps: experiment tracking, reproducible training, model/asset registry, safe rollout, and automated retraining triggers
  • Enforce data governance & security policies and contribute metadata, lineage, and definitions to the ED&A catalog
  • Optimize cost/performance across Snowflake/Snowpark and Databricks
  • Follow robust and established version control and DevOps practices
  • Create clear runbooks and documentation, and share best practices with analytics, data engineering, and product partners
MANAGEMENT & SUPERVISORY RESPONSIBILTIES
  • Direct supervisor job title(s) typically include: VP, Marketing Analytics
  • Job may require managing Analytics associates
JOB QUALIFICATIONS: Essential Skills, Abilities, and Example Behavior(s)

DELIVER QUALITY RESULTS: Able to deliver top quality service to all customers (internal and external); Able to ensure all details are covered and adhere to company policies; Able to strive to do things right the first time; Able to meet agreed‑upon commitments or advises customer when deadlines are jeopardized; Able to define high standards for quality and evaluate products, services, and own performance against those standards

TAKE INITIATIVE: Able to exhibit tendencies to be self‑starting and not wait for signals; Able to be proactive and demonstrate readiness and ability to initiate action; Able to take action beyond what is required and volunteers to take on new assignments; Able to complete assignments independently without constant supervision

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