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Flexible Remote Machine Learning Engineer Jobs in Atlanta, GA

KPMG

Director, AI Engineer

Atlanta, GA · On-site +1

Professional AI Architect, Machine Learning Engineer) or equivalent are a plus * Advanced degree from an accredited college or university in computer science, data science, engineering, or related ...

Motorola

Senior DevOps Engineer (US REMOTE)

Atlanta, GA · Remote

$140K - $170K/yr

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Zeta Global

Senior Data Scientist

Atlanta, GA · On-site +1

$160K - $180K/yr

THE ROLE The machine learning team sits at the heart of our technology and delivers on the core ... Independent engineer, capable of owning projects from an idea to design and final implementation ...

YO AI Labs

AI Data Scientist Expert - Remote

Atlanta, GA · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Science Expert - Remote

Atlanta, GA · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Cisco

Senior Software Engineer (Remote)

Atlanta, GA · Remote

$117K - $155K/yr

Familiarity with LLMs, AI agents, embeddings, or other machine-learning capabilities and their ... Exempt employees participate in Cisco's flexible vacation time off program, which has no defined ...

Crowe LLP

Cyber AI Security Manager

Atlanta, GA · On-site +1

$106K - $144K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... Act as the security expert in designing, developing, and deploying secure AI and machine learning ...

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All JobsMachine Learning Engineer JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in Atlanta, GA

Flexible Remote Machine Learning Engineer information

See Atlanta, GA salary details

$30.3K

$123.8K

$186.1K

How much do flexible remote machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for flexible remote machine learning engineer in Atlanta, GA is $123,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $149,100.00 per year, depending on experience, location, and employer.

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

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

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Atlanta, GA?

For Flexible Remote Machine Learning Engineer jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Atlanta, GA look for?

The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Flexible Remote Machine Learning Engineer jobs?

Cities near Atlanta, GA with the most Flexible Remote Machine Learning Engineer job openings:

Flexible Remote Machine Learning Engineer jobs near you
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 2% Contract, and 1% Nights. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution, with an average salary of $123,832 per year, or $59.5 per hour.

Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas

Atlanta, GA • Remote

$65 - $89/hr

Full-time

Re-posted 18 days ago

Job description

Google Cloud AI Solutions Architect, Gemini Enterprise


Overview

We are seeking a hands-on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and agentic AI solutions for end clients. This is a client-facing technical delivery role focused on applied AI/ML implementation, not sales.

The right candidate will have strong Google Cloud experience, hands-on Gemini Enterprise or Google Cloud generative AI implementation experience, and the ability to translate client workflows into secure, scalable, production-ready AI solutions. This person should be comfortable moving between architecture, coding, prototyping, configuration, integration, and client-facing technical delivery.


Responsibilities

  • Design, build, configure, and implement Gemini Enterprise solutions for end clients.
  • Develop AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows.
  • Build prototypes and proofs of concept that can be iterated into production-ready solutions.
  • Design and implement applied AI/ML solutions using Gemini Enterprise, Vertex AI, and related Google Cloud AI services.
  • Build and deploy LLM-powered applications, AI agents, retrieval-augmented generation workflows, and enterprise AI integrations.
  • Evaluate model options, agent patterns, grounding strategies, retrieval approaches, and integration paths based on client use cases.
  • Configure and deploy Gemini Enterprise agents, integrations, and related Google Cloud AI services.
  • Integrate AI agents with enterprise systems, data sources, APIs, and business applications.
  • Lead technical discovery with clients and translate requirements into solution architecture and implementation plans.
  • Develop scripts, connectors, workflows, or lightweight applications needed to support AI agent implementation.
  • Support model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness.
  • Apply best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment.
  • Communicate technical recommendations clearly to client engineering, data, security, cloud, and business stakeholders.


Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related field; equivalent practical experience will also be considered.
  • 5+ years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or hands-on client-facing technical delivery.
  • 3+ years of experience working with Google Cloud Platform.
  • Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.
  • Hands-on experience implementing Gemini Enterprise or Google Cloud generative AI solutions.
  • Hands-on experience designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or related tools.
  • Experience building, configuring, deploying, or integrating AI agents, generative AI applications, LLM-powered applications, or enterprise AI workflows.
  • Experience building agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or related agent development tools.
  • Experience with core agentic AI implementation patterns such as retrieval-augmented generation, prompt engineering, tool use/function calling, API integrations, enterprise system integration, and/or multi-agent workflows.
  • Experience with LLM application development, embeddings, model evaluation, prompt optimization, and production AI/ML implementation patterns.
  • Strong understanding of Google Cloud AI and data services, such as Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services.
  • Ability to code, script, prototype, and troubleshoot technical solutions in client environments.
  • Experience working directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions.
  • Strong understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices.
  • Excellent communication skills with the ability to explain complex technical concepts clearly.
  • Must be a U.S. Citizen.


Preferred Skills

  • Google Cloud Generative AI Leader certification.
  • Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands-on implementation architect.
  • Experience with Python, JavaScript, TypeScript, or similar programming languages.
  • Experience with data integration, workflow automation, enterprise applications, embeddings, vector search, semantic search, model grounding, enterprise search, or retrieval-augmented generation pipelines.
  • Experience in consulting, systems integration, professional services, or client-facing technical delivery.
  • Familiarity with infrastructure as code, CI/CD, containers, serverless architecture, and cloud-native application deployment.


Additional Information

This position is open to direct candidates only. We are not working with third-party agencies, subcontractors, or C2C arrangements for this role.


Candidates must be U.S. Citizens.