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Remote Kubeflow Jobs in Georgia (NOW HIRING)

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

... MLFlow, Kubeflow, Databricks, or SageMaker. * Strong Coding Skills: Expert in Python and SQL ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Site Reliability Engineer

Atlanta, GA · On-site +1

$54.75 - $72.75/hr

... Kubeflow, Kafka, OpenSearch, databases, and many others. Automation for us is a software ... Globally remote role The role We deploy and run OpenStack, Kubernetes, storage solutions, and open ...

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... Kubeflow) and model versioning practices Develop tools and frameworks to streamline ML research ...

Remote Kubeflow information

What is a remote Kubeflow?

A Remote Kubeflow job refers to a role where professionals use Kubeflow, an open-source machine learning platform designed for Kubernetes, while working remotely. These jobs typically involve designing, deploying, and managing machine learning workflows on cloud or on-premises Kubernetes clusters. Responsibilities may include automating ML pipelines, optimizing model training, and collaborating with data scientists and engineers. Remote Kubeflow professionals usually need expertise in Kubernetes, Docker, Python, and machine learning concepts. The remote aspect allows them to perform these tasks from anywhere with reliable internet access.

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

To thrive as a Remote Kubeflow Engineer, you need strong expertise in machine learning, cloud computing, and container orchestration, typically supported by a degree in computer science or related fields. Proficiency with tools such as Kubeflow, Kubernetes, Docker, and cloud platforms like AWS, GCP, or Azure—as well as experience with CI/CD pipelines—is essential. Strong problem-solving skills, communication, and the ability to collaborate remotely are important soft skills for success. These skills ensure the effective deployment and management of scalable machine learning workflows in distributed, cloud-based environments.

What are some common challenges faced by professionals working in a remote Kubeflow engineer role?

Remote Kubeflow engineers often encounter challenges such as troubleshooting distributed machine learning pipelines without direct, on-premises access to infrastructure. Effective communication with data scientists, DevOps, and other stakeholders can also be more complex due to differing time zones and remote collaboration tools. Additionally, managing secure access and ensuring seamless deployment of ML workflows in cloud environments requires a strong understanding of both Kubernetes and Kubeflow. Overcoming these challenges typically involves proactive documentation, regular virtual meetings, and a collaborative approach to problem-solving.

What is the difference between Remote Kubeflow vs Remote Data Scientist?

AspectRemote KubeflowRemote Data Scientist
Required CredentialsCloud certifications, Kubernetes, ML OpsStatistics, Machine Learning, Programming
Work EnvironmentCloud platforms, DevOps toolsData analysis, modeling, research
Industry UsageAI/ML deployment, MLOps teamsData analysis, predictive modeling

Remote Kubeflow focuses on deploying and managing ML workflows using Kubernetes, requiring cloud and DevOps skills. Remote Data Scientists analyze data, build models, and interpret results. While both roles involve machine learning, Remote Kubeflow emphasizes deployment and infrastructure, whereas Remote Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Kubeflow jobs in Georgia?

The most popular types of Kubeflow jobs in Georgia are:

What cities in Georgia are hiring for Remote Kubeflow jobs?

Cities in Georgia with the most Remote Kubeflow job openings:

Staff Machine Learning Engineer

PrizePicks

Atlanta, GA • On-site, Remote

$220K - $280K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago


Job description

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?
As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.
What you'll do:
  • Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
  • Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
  • Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
  • End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.
What you have:
  • 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments.
  • 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms.
  • Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
  • MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker.
  • Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers.
  • Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.
What makes you stand out:
  • Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection.
  • Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
  • Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
Where you'll live:
  • While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote
Working at PrizePicks:
The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.
This application period will remain open for 30 days. We're committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.
Date Posted: 4/16/2026
1st Extension: 5/16/2026
2nd Extension: 6/16/2026
Benefits you'll receive:
In addition to your great compensation package, full-time employees will be eligible for the following perks:
  • Company-subsidized medical, dental, & vision plans
  • 401(k) plan with company match
  • Annual bonus
  • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
  • Generous paid leave programs, including 16-week paid parental leave and disability benefits
  • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
  • Company-wide in-person events and team outings
  • Lifestyle enhancement program
  • Company equipment provided (Windows & Mac options)
  • Annual performance reviews with opportunities for growth and career development

You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.