2

Remote Mlops Jobs in Georgia (NOW HIRING)

Lead Machine Learning Engineer - REMOTE

Atlanta, GA · Remote

$98K - $129K/yr

The ideal candidate is a software engineer with deep MLOps expertise. They know how to design model ... Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or ...

Lead Machine Learning Engineer - REMOTE

Atlanta, GA · On-site +1

$98K - $129K/yr

The ideal candidate is a software engineer with deep MLOps expertise. They know how to design model ... Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or ...

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud Platforms: Strong hands-on experience with AWS and Azure * Regulated Environments: Experience ...

Senior DevOps Engineer

Atlanta, GA · On-site +1

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud Platforms: Strong hands-on experience with AWS and Azure * Regulated Environments: Experience ...

Senior DevOps Engineer

Atlanta, GA · On-site +1

$125K - $160K/yr

Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud Platforms: Strong hands-on experience with AWS and Azure * Regulated Environments: Experience ...

Senior Agentic (AI) Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and ... All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

next page

Showing results 1-20

Remote Mlops information

What is the difference between Remote Mlops vs Data Engineer?

AspectRemote MlopsData Engineer
Required CredentialsCertifications in cloud platforms, ML frameworks, scripting skillsDatabase, ETL, SQL, cloud certifications
Work EnvironmentRemote, cloud-based, collaboration with ML teamsRemote or on-site, data infrastructure focus
Industry UsageAI/ML companies, tech firms, startupsData-driven companies, finance, healthcare, tech
Common Search/ComparisonYesYes

Remote Mlops and Data Engineers share overlapping skills like cloud computing and scripting, but Remote Mlops focuses on deploying and maintaining ML models in production, while Data Engineers build and manage data pipelines. Both roles are essential in data-driven organizations, often collaborating but with distinct technical focuses.

What are the key skills and qualifications needed to thrive as a remote mlops engineer?

To thrive as a Remote MLOps Engineer, you need a strong background in machine learning, software engineering, and cloud computing, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and experience with ML frameworks such as TensorFlow or PyTorch are crucial, along with relevant certifications. Excellent communication, problem-solving abilities, and self-motivation are essential soft skills for collaborating across distributed teams and handling complex deployments. These skills ensure the seamless integration, deployment, and monitoring of machine learning models in production environments, driving efficiency and reliability in remote settings.

Is remote MLOps in high demand?

Remote MLOps roles are in high demand due to the increasing adoption of machine learning and AI across industries. Employers seek professionals skilled in cloud platforms, automation, and tools like Docker and Kubernetes to manage and deploy ML models efficiently in remote environments.

What is a remote mlops?

A Remote MLOps job involves managing and automating the deployment, monitoring, and maintenance of machine learning models in production environments, all while working from a remote location. MLOps stands for Machine Learning Operations, and professionals in this role bridge the gap between data science and IT operations to ensure smooth, reliable model performance. Remote MLOps engineers use tools and practices to streamline machine learning workflows, collaborate with distributed teams, and maintain infrastructure without being tied to a physical office.

What are some common challenges faced by remote mlops engineers, and how can they be overcome?

Remote MLOps engineers often face challenges related to collaborating across distributed teams, ensuring robust CI/CD pipelines for machine learning models, and maintaining secure, scalable cloud infrastructure. Effective communication using collaboration tools and thorough documentation is key to overcoming team coordination issues. Additionally, leveraging cloud-based MLOps platforms and automating routine processes can help streamline workflows and reduce operational friction, allowing engineers to focus on innovation and model optimization.
What are the most commonly searched types of Mlops jobs in Georgia? The most popular types of Mlops jobs in Georgia are:
What job categories do people searching Remote Mlops jobs in Georgia look for? The top searched job categories for Remote Mlops jobs in Georgia are:
What cities in Georgia are hiring for Remote Mlops jobs? Cities in Georgia with the most Remote Mlops job openings:
Infographic showing various Remote Mlops job openings in Georgia as of August 2026, with employment types broken down into 66% Full Time, and 34% Contract. Highlights an 100% Remote job distribution.

Lead Machine Learning Engineer - REMOTE

Lennar

Atlanta, GA • Remote

$98K - $129K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 4 days ago


Lennar rating

8.0

Company rating: 8.0 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

19th of 80 rated construction


Job description

Lead ML Engineer - REMOTE

We are Lennar

Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500 company and consistently ranked among the top homebuilders in the United States.

Join a Company that Empowers you to Build your Future

Lennar is seeking a Machine Learning Engineer to own and evolve the infrastructure and surface mechanisms that take our data science and ML models from notebook to production. This is a key role on the Applied AI & Data Science team, sitting at the intersection of software engineering, ML platform, and applied data science.

The ideal candidate is a software engineer with deep MLOps expertise. They know how to design model serving for both batch and real-time inference, build durable model registries and versioning practices, and stand up retraining pipelines that data scientists actually use. They are hands-on with AWS SageMaker (including SageMaker Unified Studio), MLflow, Weights & Biases, and the surrounding tooling that makes ML systems reliable in production.

You'll partner closely with data scientists, AI engineers, and platform teams-building and setting the foundation that lets ML models ship faster, retrain on schedule, and operate with the same engineering rigor as any other production service across 40+ divisions of one of the nation's largest homebuilders.

  • A career with purpose.

  • A career built on making dreams come true.

  • A career built on building zero defect homes, cost management, and adherence to schedules.

Your Responsibilities on the Team

  • Design, build, and set the ML platform surface used by our data science team-covering model packaging, deployment, batch and real-time inference, and observability.

  • Establish and evangelize ML platform standards, patterns, and reusable components-raising the engineering bar for how ML models are built, deployed, and operated across the organization.

  • Mentor data scientists and engineers on production ML practices, code review their platform-adjacent work, and serve as the technical authority on MLOps decisions.

  • Own model serving infrastructure on AWS SageMaker (including SageMaker Unified Studio)-building patterns for batch inference jobs, real-time endpoints, and serverless inference depending on workload requirements.

  • Build and maintain the model registry, version control, and promotion workflows that move models cleanly from development to staging to production with full lineage and auditability.

  • Stand up and operate retraining pipelines using MLflow, Weights & Biases, and orchestration tools-automating retraining triggers, experiment tracking, model evaluation, and approval gates.

  • Build monitoring and alerting for production models including drift detection, performance degradation, data quality issues, and latency or cost anomalies.

  • Write clean, modular Python and infrastructure-as-code (Terraform) for ML platform components, applying software engineering best practices including testing, versioning, and code review.

  • Partner closely with data scientists to make their workflow faster and more reliable-reducing time-to-production for new models and increasing confidence in models already in production.

  • Collaborate with Data / Platform Engineering and AI Engineering counterparts to ensure feature pipelines, model artifacts, and inference services are integrated cleanly with the broader data and AI platform.

Requirements

  • Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.
  • 7+ years of software engineering experience, including meaningful production ownership of services or platforms in a cloud environment.
  • 5+ years of hands-on MLOps or ML platform experience-deploying, monitoring, and retraining production models at scale.
  • Strong hands-on experience with AWS SageMaker (Unified Studio strongly preferred), including model training jobs, endpoints, batch transform, and pipelines.
  • Deep experience with experiment tracking, model registries, and retraining workflows using MLflow, Weights & Biases, or comparable tooling.
  • Strong Python skills with a track record of writing modular, well-tested, production-ready code; experience with infrastructure-as-code (Terraform preferred).
  • Solid understanding of both batch and real-time inference patterns, including the tradeoffs between latency, throughput, cost, and operational complexity.
  • Proven ability to partner with data scientists-understanding their workflow, lowering friction, and translating modeling needs into reliable platform capabilities.
  • Comfortable operating with autonomy in ambiguous environments-scoping work, setting realistic timelines, and raising blockers proactively without waiting to be asked.
  • Bonus: Experience with feature stores, model gateways, GPU workloads, distributed training, model drift monitoring tools, or supporting both classical ML and LLM-based models on the same platform.

What we offer:

  • The opportunity to deliver impact across one of the largest homebuilders in the United States.
  • A corporate culture focused on growth and development.
  • Freedom to try new impactful ideas.
  • Ability to deploy your work to teams across 40+ divisions and interact directly with those teams.
  • End-to-end project ownership.
  • Occasional travel for team activities and meetings.
  • Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or Dallas, TX.
  • Healthcare (medical, dental, vision) and 401k matching

Life at Lennar

At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar's policies and applicable plan terms. Visit Lennartotalrewards.com to view our suite of benefits.

Join the fun and follow us on social media to see what's happening at our company, and don't forget to connect with us on Lennar: Overview | LinkedIn for the latest job opportunities.

Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.


What Lennar employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Lennar logo

About Lennar

Sourced by ZipRecruiter

Since 1954, Lennar has built over one million new homes for families across America. We build in some of the nation’s most popular cities, and our communities cater to all lifestyles and family dynamics, whether you are a first-time or move-up buyer, multigenerational family, or Active Adult.

Industry

Construction

Company size

5,001 - 10,000 Employees

Headquarters location

Miami, FL, US

Year founded

1954

Social media