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Remote Deep Learning Engineer Jobs in Atlanta, GA

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

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 ...

... deep learning, motion planning, grasp planning, navigation, and SLAM technologies. Unique among early-stage startups, Dorabot employs engineers and business professionals from over 10 different ...

... deep learning, motion planning, grasp planning, navigation, and SLAM technologies. Unique among early-stage startups, Dorabot employs engineers and business professionals from over 10 different ...

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Showing results 1-20

Remote Deep Learning Engineer information

See Atlanta, GA salary details

$10.6K

$80.7K

$134.6K

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

As of Jun 10, 2026, the average yearly pay for remote deep learning engineer in Atlanta, GA is $80,669.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,200.00 and $133,700.00 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 cities near Atlanta, GA are hiring for Remote Deep Learning Engineer jobs? Cities near Atlanta, GA with the most Remote Deep Learning Engineer job openings:
Infographic showing various Remote Deep Learning Engineer job openings in Atlanta, GA as of June 2026, with employment types broken down into 61% Full Time, 34% Part Time, 2% Temporary, and 3% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution, with an average salary of $80,669 per year, or $38.8 per hour.
Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture

Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture

Autodesk

Atlanta, GA • Remote

Full-time

Posted 7 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

7th of 188 rated software companies


Job description

Job Requisition ID #

26WD94803Senior Principal Machine Learning Engineer, ML Platform and Systems ArchitecturePosition Overview

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.

Autodesk is seeking a Senior Principal ML Engineer, ML Platform and Systems Architecture to define and drive the technical strategy for large-scale machine learning platforms and systems. This is a top-level engineering leadership role for a technical authority who can shape multi-year architecture, influence engineering standards across teams, and lead major platform initiatives that connect research, product, and business goals.

You will be responsible for driving the evolution of the systems that enable machine learning across Autodesk, including training infrastructure, data platforms, evaluation and experimentation systems, model serving frameworks, and operational excellence for production ML. You will work across organizational boundaries to guide decisions, resolve hard technical challenges, and ensure that platform investments are aligned with long-term product and business outcomes.

This role is fully remote-friendly, with team members distributed across the US and Canada.

Location: US or Canada Remote

Responsibilities
  • Define and lead technical strategy for a domain or large-scale platform supporting machine learning systems
  • Drive architecture decisions across teams for scalable training, data, evaluation, deployment, observability, and reliability systems
  • Lead multi-team initiatives with far-reaching technical impact across a function, platform, or division
  • Define technical direction for data pipelines that support large-scale structured and semi-structured technical datasets
  • Set standards for data lineage, provenance, governance, and responsible data usage in ML systems
  • Lead architecture for distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
  • Define scalable approaches for model deployment, inference services, monitoring, and observability for production ML systems
  • Influence platform direction for ML-ready representations of geometry, graph, hierarchical, or multimodal data
  • Influence standards for engineering quality, architecture, resiliency, risk management, and operational excellence
  • Identify long-term technical and operational risks and guide investment decisions that future-proof platform capabilities
  • Serve as a technical authority and trusted advisor to engineering leaders, senior engineers, and cross-functional stakeholders
  • Resolve complex cross-team technical problems by framing options, aligning stakeholders, and driving execution
  • Champion engineering practices that improve service quality, release readiness, monitoring, incident response, and maintainability
  • Mentor senior engineers and help build the next level of technical leadership within the organization
  • Clearly articulate the business rationale for technical investments and ensure alignment with broader organizational goals
Minimum Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience
  • At least 8 years of industry experience in software engineering, ML platform architecture, distributed systems, or related domains, including experience driving architecture, cross-team technical direction, and large-scale platform outcomes
  • Significant experience in software architecture, distributed systems, platform engineering, or ML infrastructure at scale
  • Deep expertise in one or more critical areas such as distributed training, data platforms, ML platform architecture, model serving, or reliability engineering
  • Proven record of leading technical strategy and delivering cross-team outcomes with broad organizational impact
  • Strong command of cloud-native architectures, production engineering practices, and large-scale system design
  • Demonstrated ability to influence architecture and engineering standards beyond a single team
  • Strong executive-level communication and the ability to connect technical direction to business priorities
Preferred Qualifications
  • Experience setting architecture direction for ML platforms used across multiple teams or organizations
  • Experience building or scaling data pipelines for large-scale structured and semi-structured technical datasets
  • Experience with data lineage, provenance, governance, and responsible data usage in ML systems
  • Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
  • Experience with model deployment, inference services, monitoring, and observability for production ML systems
  • Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data
  • Experience building or scaling foundation model infrastructure and high-throughput data systems
  • Experience leading engineering improvements around resiliency, service reviews, fire drills, and risk reduction
  • Familiarity with AEC, design technology, BIM/CAD ecosystems, or Autodesk products
  • External technical leadership through architecture leadership, speaking, or domain expertise is a plus
The Ideal Candidate
  • Is a deeply technical leader who still operates effectively in hands-on engineering contexts
  • Thinks in systems, platforms, and multi-year strategy
  • Leads through influence, judgment, and clarity
  • Builds alignment across teams while holding a high bar for technical excellence

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk - it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/

Salary transparency

Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $178,875 and $320,650. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Equal Employment Opportunity

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

Diversity & Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging

Are you an existing contractor or consultant with Autodesk?

Please search for open jobs and apply internally (not on this external site).


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About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982