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Research Assistant Deep Learning Jobs in Atlanta, GA

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

... deep learning algorithms for virtual staining and digital pathology applications Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative ...

Dolby

Senior Audio AI Researcher

Atlanta, GA · On-site

$88K - $120K/yr

Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions. Requirements * Ph.D. in Computer Science or ...

Dolby

Research Scientist- Spatial Audio & AI

Atlanta, GA · On-site

$140 - $170/hr

Develop and combine deep learning methodologies with perceptually relevant signal processing and metrics. * Partner with ATG researchers, develop solutions for the relevant applications. What you ...

Cox Automotive

Machine Learning Lead Engineer

Redan, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

Cox Automotive

Machine Learning Lead Engineer

Conley, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

Cox Automotive

Machine Learning Lead Engineer

Atlanta, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

Cox Automotive

Machine Learning Lead Engineer

Smyrna, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

Cox Automotive

Machine Learning Lead Engineer

Austell, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

May assist with or lead the development of industry whitepapers or other technical publications ... Deep expertise in multiple ML domains and familiarity with emerging research areas * Strong ...

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Research Assistant Deep Learning information

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How much do research assistant deep learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for research assistant deep learning in Atlanta, GA is $21.07, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $24.52 per hour, depending on experience, location, and employer.

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.

What are the key skills and qualifications needed to thrive as a research assistant deep learning?

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What are popular job titles related to Research Assistant Deep Learning jobs in Atlanta, GA?

For Research Assistant Deep Learning jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Research Assistant Deep Learning jobs in Atlanta, GA look for?

The top searched job categories for Research Assistant Deep Learning jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Research Assistant Deep Learning jobs?

Cities near Atlanta, GA with the most Research Assistant Deep Learning job openings:

Research Assistant Deep Learning jobs near you
Infographic showing various Research Assistant Deep Learning job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $43,824 per year, or $21.1 per hour.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted 29 days ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.