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Online Machine Learning Jobs in Georgia (NOW HIRING)

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We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

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We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... Some of the core areas of focus for our team include pricing, online advertising, uplift and ...

New

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All JobsOnline Machine Learning JobsOnline Machine Learning Jobs in Georgia

Online Machine Learning information

What is online machine learning?

Online machine learning is a method where models are trained incrementally as new data becomes available, rather than being trained all at once on a fixed dataset. This approach is particularly useful in environments where data arrives continuously, such as real-time analytics, recommendation systems, and fraud detection. Online learning algorithms update their knowledge with each new data point, allowing them to adapt quickly to changes and trends. This makes them ideal for applications that require immediate responses and adaptability to evolving data streams.

What are the key skills and qualifications needed to thrive as an online machine learning engineer?

To excel as an Online Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning algorithms, often supported by a relevant degree and experience with streaming data. Familiarity with tools such as Apache Kafka, Spark Streaming, Python, TensorFlow, and real-time data processing frameworks is critical. Problem-solving ability, adaptability, and effective communication are essential soft skills for collaborating with multidisciplinary teams and responding to rapidly changing data. These competencies are crucial for building scalable, responsive models that provide timely insights in dynamic production environments.

How does collaboration typically work between online machine learning engineers and data scientists in a project setting?

Online machine learning engineers often work closely with data scientists to ensure that the models they develop can be effectively deployed and updated in real-time environments. While data scientists may focus on feature engineering, model selection, and initial training using historical data, online machine learning engineers are responsible for integrating these models into production systems and implementing mechanisms for continuous learning from live data streams. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration and ensure that the models remain accurate and efficient as new data arrives.

What is the difference between Online Machine Learning vs Data Scientist?

AspectOnline Machine LearningData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related fields; certifications in ML or data analysisBachelor's or master's in CS, statistics, or related fields; advanced degrees often preferred
Work EnvironmentTech companies, startups, research labs; focus on real-time data processingCorporate, consulting, or research settings; focus on data analysis and modeling
Industry UsageMachine learning applications, AI development, real-time systemsData analysis, predictive modeling, business insights

Online Machine Learning specialists focus on developing algorithms that learn continuously from streaming data, often in real-time environments. Data Scientists analyze large datasets to extract insights, build models, and support decision-making. While both roles require knowledge of machine learning, Online Machine Learning emphasizes real-time data processing, whereas Data Scientists focus on data analysis and modeling for strategic insights.

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

The most popular types of Machine Learning jobs in Georgia are:

What cities in Georgia are hiring for Online Machine Learning jobs?

Cities in Georgia with the most Online Machine Learning job openings:

Online Machine Learning jobs near you
Infographic showing various Online Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 21% Part Time, 6% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Next Insurance - Machine Learning Engineer

Beyond SOF

Atlanta, GA • On-site

Full-time

Re-posted 26 days ago

Job description

Machine Learning Engineer
Experience level: Mid-senior
Experience required: 4 Years
Education level: Bachelor's degree
Job function: Information Technology
Industry: Financial Services
Total position: 1
Relocation assistance: Limited assistance
Visa : Only US citizens and Greencard holders
Job Summary
We are looking for a driven Machine Learning Engineer to help us bring software development rigor to the ML life-cycle within the business insurance industry. As an experienced innovator partnering with the marketing and growth teams, this is a massive opportunity to drive high growth impact at a hyper-growth startup. Your job is to be a full stack ML engineer, supercharging all aspects of scaling Machine Learning at NEXT: application design and architecture, scalable deployment of inference solutions as APIs, data enrichment as a service, and model monitoring.
You will be joining an innovative division of NEXT based in Atlanta: Data Labs. The mandate of Data Labs is to build software and data solutions that meaningfully impact marketing, funnel, risk, and servicing/claims experiences.
What You'll Do:
  • Empower our team of data scientists to rapidly develop and deploy ML solutions.
  • Leverage software engineering best-practices to create and deploy data-intensive and machine learning inference products.
  • Understand the data and dig deep to extract actionable insights.
  • Think creatively and outside the box to answer desired experimental questions as well as exposing opportunities to create business value.
  • Work cross-functionally with marketing, engineering, product, senior management, and external partners.

What We Need:
  • 3+ years of hands-on experience in the complete software development life-cycle with demonstrated professional experience with machine learning
  • Strong command of Python and the standard web development frameworks (e.g. Django, Flask, FastAPI) & fluency with database technologies, SQL, and Python data packages
  • Demonstrated experience deploying models and applications to a cloud environment using tools like Docker and Kubernetes.
  • Demonstrated experience with software engineering best-practices, such as Test-Driven Development and continuous integration/deployment pipelining
  • Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)

Unstoppable Qualities:
  • Experience in the insurance industry (strong fintech/lending experience will also be considered)
  • Experience with GitLab

Apply