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Remote Deep Learning Engineer Jobs in Georgia (NOW HIRING)

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Machine Learning Platform Engineer

Atlanta, GA · On-site +1

$135K - $160K/yr

MLOps Expertise , deep experience building a platform for managing the full ML lifecycle (training ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

BSC Analytics

$150K - $175K/yr

Engineering Employment Type: Full Time Location: Remote (USA) Compensation: $150,000 - $175,000 ... remote-first culture that values deep expertise, autonomy, and continuous learning. Key ...

BSC Analytics

$150K - $175K/yr

Engineering Employment Type: Full Time Location: Remote (USA) Compensation: $150,000 - $175,000 ... remote-first culture that values deep expertise, autonomy, and continuous learning. Key ...

SynergisticIT

AI / ML Engineer

Atlanta, GA · On-site +1

With remote work and global talent pools, even entry-level roles receive hundreds of applications ... Data Scientists & Machine Learning Engineers * Data Engineers * Required & Preferred Skills * Java ...

Almost Fun

Our mission is to engage students in their learning and help them apply their education to ... Our software engineers will : * Participate in a weekly team reading group focused on research on ...

Almost Fun

Our mission is to engage students in their learning and help them apply their education to ... Our software engineers will : * Participate in a weekly team reading group focused on research on ...

IPA

Corporate Learning & Development Manager

Duluth, GA · On-site +1

Hybrid (M-F: 3 days on-site, 2 days remote) OR Remote Salary: $100,000-$110,000 + Bonus Eligible ... Enterprise Leadership Development Programming * Architect and execute a scalable, enterprise-wide ...

ICF

Senior Transmission Line Engineer - REMOTE

Atlanta, GA · Remote

$100K - $138K/yr

Title: Senior Transmission Line Engineer Location: Remote US Ready to make a difference? We are ... Committed to continuous learning and process improvement, consistently seeking opportunities to ...

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All JobsDeep Learning Engineer JobsRemote Deep Learning Engineer JobsRemote Deep Learning Engineer Jobs in Georgia

Remote Deep Learning Engineer information

See Georgia salary details

$9.3K

$70.8K

$118.2K

How much do remote deep learning engineer jobs pay per year?

As of Jun 17, 2026, the average yearly pay for remote deep learning engineer in Georgia is $70,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,800.00 and $117,400.00 per year, depending on experience, location, and employer.

How do Remote Deep Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

What are the key skills and qualifications needed to thrive as a Remote Deep Learning Engineer, and why are they important?

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What is a Remote Deep Learning Engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.
What are popular job titles related to Remote Deep Learning Engineer jobs in Georgia? For Remote Deep Learning Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning Engineer jobs in Georgia look for? The top searched job categories for Remote Deep Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Remote Deep Learning Engineer jobs? Cities in Georgia with the most Remote Deep Learning Engineer job openings:
Remote Deep Learning Engineer jobs near you
Infographic showing various Remote Deep Learning Engineer job openings in Georgia as of June 2026, with employment types broken down into 60% Full Time, 33% Part Time, 2% Temporary, and 5% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $70,831 per year, or $34.1 per hour.

Enterprise AI Engineer (GCP)

INFT Solutions Inc

Atlanta, GA • On-site, Remote

Contractor

Posted 12 days ago

Job description

Job Description: Enterprise AI Engineer (GCP)
Location: Remote / Hybrid Focus: Agentic AI, Data Intelligence, and Enterprise Scale
Role Overview
We are looking for a Principal Enterprise AI Engineer to architect and deliver high-impact AI
solutions within the Google Cloud ecosystem. This role is designed for a technical leader who
can bridge the gap between complex data landscapes and autonomous AI systems. You will lead
the development of Agentic AI frameworks and Data Intelligence platforms that drive
significant digital transformation for global enterprise clients.
Core Responsibilities
 Architect Agentic Systems: Design and deploy multi-agent orchestration frameworks
using Vertex AI Agent Builder, LangGraph, or CrewAI to automate complex, multi-step
business workflows.
 Master RAG Architectures: Build and optimize high-performance Retrieval-
Augmented Generation (RAG) systems, ensuring LLMs are grounded in enterprise data
across BigQuery and Databricks.
 Model Strategy & Optimization: Select and fine-tune models within the Gemini 1.5
family, balancing high-reasoning capabilities (Pro) with high-speed efficiency (Flash) for
production-grade latency.
 Legacy Transformation: Lead the strategic migration of legacy analytics logic (e.g.,
SAS environments) into modern, AI-powered cloud architectures.
 GTM Collaboration: Work closely with Go-To-Market (GTM) leadership to translate
technical AI roadmaps into measurable business value for C-suite stakeholders.
Required Skill Requirements
1. Agentic AI & Orchestration
 Framework Mastery: Expert implementation of LangChain, LangGraph, or
LlamaIndex for stateful, autonomous agent development.
 Advanced Prompting: Proficiency in Chain-of-Thought (CoT), ReAct patterns, and
system instruction optimization to ensure reliable model output.
 Function Calling: Experience building custom tools that allow LLMs to interact
securely with enterprise APIs and SQL databases.
2. Data Intelligence & Engineering
 Hybrid Data Ecosystems: Deep experience integrating Google Cloud AI services with
Databricks (Delta Lake) for unified data intelligence.
 Vector Engineering: Proficiency with Vertex AI Vector Search (formerly Matching
Engine) and embedding strategies for large-scale semantic search.
 Data Flow: Skill in building scalable pipelines using Dataflow or Spark to process
unstructured data for AI readiness.
3. LLMOps & Production Engineering
 Evaluation Frameworks: Ability to build automated "LLM-as-a-judge" evaluation
pipelines to track accuracy, faithfulness, and hallucination rates.
 Cloud Infrastructure: Mastery of the Vertex AI suite (Studio, Model Garden, Pipelines)
and Infrastructure as Code (Terraform).
 Programming: Expert-level Python (FastAPI, Pydantic) and advanced SQL.
4. Strategic Governance
 Responsible AI: Implementation of safety filters, PII redaction, and ethical AI
monitoring.
 Business Translation: Ability to convert technical metrics (latency, token costs) into
business KPIs (ROI, process efficiency).
Qualifications
 Experience: 8+ years in Software Engineering or Data Science, with at least 3+ years
focused on production-grade AI/ML.
 Education: B.S./M.S. in Computer Science, AI, or a related quantitative field.
 Certifications: Google Professional Machine Learning Engineer or Professional Cloud
Architect (preferred).
Technology Stack
 AI/ML: Vertex AI, Gemini 1.5 Pro/Flash, PyTorch.
 Data: BigQuery, Databricks, Vertex Vector Search.
 Orchestration: LangGraph, Vertex AI Agent Builder.
 DevOps: GitHub Actions, Terraform, Vertex AI Pipelines.