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Remote Bioinformatics Machine Learning Jobs in Georgia

Home Depot

Senior AI Engineer (Remote)

Atlanta, GA · On-site +1

$99K - $136K/yr

  • Medical

  • Retirement

  • PTO

Operating at the intersection of Data Science, Machine Learning Engineering, and Software Engineering, this hands-on role translates AI concepts into enterprise-ready products. This role involves ...

Adidev Technologies Inc

ML/AI Engineer

Alpharetta, GA · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Adidev Technologies Inc

ML/AI Engineers

Atlanta, GA · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

YO AI Labs

AI Data Scientist Expert - Remote

Atlanta, GA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... 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

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Dlapiper

Data Scientist

Atlanta, GA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

New

Honeywell

Sr Advanced Data Scientist

Atlanta, GA · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ... Experience working with remote and global teams * Results driven with a positive can-do attitude ...

Honeywell

Sr Advanced Data Scientist

Atlanta, GA · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems ... Experience working with remote and global teams * Results driven with a positive can-do attitude ...

Trella Health

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

S. locations in a remote capacity. Reports to: Chief Technology Officer As the VP of Data Strategy ... AI & Machine Learning * Build and scale the organization's AI/ML capabilities, including ...

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All JobsBioinformatics Machine Learning JobsRemote Bioinformatics Machine Learning JobsRemote Bioinformatics Machine Learning Jobs in Georgia

Remote Bioinformatics Machine Learning information

What is a remote bioinformatics machine learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

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

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

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

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

What are popular job titles related to Remote Bioinformatics Machine Learning jobs in Georgia?

For Remote Bioinformatics Machine Learning jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Remote Bioinformatics Machine Learning jobs in Georgia look for?

The top searched job categories for Remote Bioinformatics Machine Learning jobs in Georgia are:

What cities in Georgia are hiring for Remote Bioinformatics Machine Learning jobs?

Cities in Georgia with the most Remote Bioinformatics Machine Learning job openings:

Remote Bioinformatics Machine Learning jobs near you
Infographic showing various Remote Bioinformatics Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior AI Engineer (Remote)

Home Depot

Atlanta, GA • On-site, Remote

$99K - $136K/yr

Full-time

Medical, Retirement, PTO

Posted 13 days ago

Home Depot rating

7.4

Company rating: 7.4 out of 10

Based on 6,436 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Senior AI Engineer is responsible for designing, building, scaling, and optimizing production-grade Agentic AI systems that drive measurable business outcomes across The Home Depot. Operating at the intersection of Data Science, Machine Learning Engineering, and Software Engineering, this hands-on role translates AI concepts into enterprise-ready products.
This role involves developing scalable applications powered by LLMs, SLMs, Retrieval-Augmented Generation (RAG) frameworks, and autonomous agents. You will build the core orchestration layers for multi-agent workflows, tool integration, and planning, alongside the infrastructure required for reliable, large-scale cloud deployment. By partnering with product, engineering, and business teams, you will rapidly prototype solutions, navigate ambiguity, and seamlessly transition cutting-edge AI capabilities from concept to production.
Required skills
  • Experience: 6+ years of experience in AI, Machine Learning Engineering, or Software Engineering with strong Python development skills and modern software engineering practices.
  • AI Delivery: Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems.
  • AI Foundations: Deep understanding of AI/ML foundations, including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases.
  • Orchestration & Integration: Experience developing orchestration layers (task execution, routing, planning, workflows) and seamlessly integrating AI solutions with enterprise platforms, APIs, and business systems.
  • Infrastructure & MLOps: Expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (e.g., Terraform), andAI pipeline design, with hands-on implementation of MLOps/LLMOps best practices (CI/CD, automated testing, model versioning and registries, governance, compliance, and security) across the full AI/agent lifecycle.
  • AIOps & Deployment Reliability: Experience building automated CI/CD pipelines for AI/agentic systems, implementing progressive rollout strategies (canary, blue-green, and shadow deployments) with automated rollback, and establishing end-to-end observability (logging, metrics, distributed tracing, and automated alerting) across models, agents, and orchestration layers to ensure production reliability, performance, and cost/token efficiency at scale.
  • Optimization & Debugging: Demonstrated ability to optimize complex AI systems for performance, reliability, scalability, latency, cost efficiency, and token use, as well as debugging operational failure modes.
  • Execution & Collaboration: Excellent cross-functional communication and collaboration skills, with a proven ability to take AI solutions from concept to production in complex enterprise environments.

Key Responsibilities:
  • 70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
  • 10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
  • 20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Direct Manager/Direct Reports:
  • This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager
  • This Position has 0 Direct Reports

Travel Requirements:
  • Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:
  • Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:
  • Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:
  • Must be eighteen years of age or older.
  • Must be legally permitted to work in the United States.

Preferred Qualifications:
  • Tools & Frameworks: Hands-on experience with Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, AutoGen, or similar orchestration tools and frameworks.
  • AI Infrastructure & Platform Tooling: Hands-on experience with infrastructure-as-code (e.g., Terraform), Kubernetes/GKE for container orchestration, GPU/accelerator provisioning and autoscaling, model registries, feature stores, and vector database operations at production scale.
  • Full-stack skills: Node.js/React/REST, API design, performance optimization, Linux, Git, modern deployment toolchain.
  • Industry Context: Background in retail, supply chain, manufacturing, eCommerce, logistics, or finance where Applied ML is mature.
  • Guardrails & Reliability: Knowledge and experience in establishing Responsible AI, evaluation frameworks, reliability engineering, and AI governance guardrails.
  • Leadership & Innovation: A proven track record of driving innovation, delivering measurable business impact, mentoring engineering teams, and establishing AI engineering standards and best practices.
  • Master's or bachelor's in computer science, Artificial Intelligence, Machine Learning, or a related technical discipline.

Minimum Education:
  • The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education:
  • No additional education

Minimum Years of Work Experience:
  • 2

Preferred Years of Work Experience:
  • No additional years of experience

Minimum Leadership Experience:
  • None

Preferred Leadership Experience:
  • None

Certifications:
  • None

Competencies:
  • Global Perspective
  • Manages Ambiguity
  • Nimble Learning
  • Self-Development
  • Collaborates
  • Cultivates Innovation
  • Situational Adaptability
  • Communicates Effectively
  • Drives Results
  • Interpersonal Savvy

Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.
For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:
The pay range for this position is between $100,000.00 - $250,000.00

What Home Depot employees say

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About Home Depot

Sourced by ZipRecruiter

The Home Depot is the world’s largest home improvement specialty retailer, operating a vast network of warehouse-format stores across the United States, Canada, and Mexico. Founded in 1978, the company has established itself as the primary resource for building materials, lawn and garden products, and home décor. Its business model caters to two distinct customer bases: Do-It-Yourself (DIY) homeowners and "Pro" customers, such as professional contractors and tradespeople. Beyond product sales, the company offers an extensive suite of services, including professional installation and one of the largest tool rental operations in North America.

Industry

Retail, manufacturing and personal services

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

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