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Freelance Nvidia Machine Learning Jobs in Georgia

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

Avani Technology Solutions, Inc.

AWS Architect

Atlanta, GA · On-site

$62.50 - $82/hr

... of Machine Learning Platforms including Public Cloud Offering • Experience with software ... with Nvidia-docker, GPU specific technologies Please share your resumes to natraj.b ...

Deloitte

Senior AI Engineer - SFL Scientific

Atlanta, GA · On-site

$100.50K - $138K/yr

... machine learning applications. Responsibilities : • Work with clients to design, develop, and ... Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc. • Live within ...

New

Honeywell

Sr Advanced AI Platform Engineer

Atlanta, GA

$117.80K - $155.30K/yr

You will work at the intersection of data engineering, machine learning operations, and edge AI ... Experience with edge AI deployment on NVIDIA Jetson or similar embedded GPU platforms. * Experience ...

Honeywell

Sr Advanced AI Platform Engineer

Atlanta, GA · On-site

$117.90K - $155.40K/yr

You will work at the intersection of data engineering, machine learning operations, and edge AI ... Experience with edge AI deployment on NVIDIA Jetson or similar embedded GPU platforms. * Experience ...

Honeywell

Sr Advanced AI Platform Engineer

Atlanta, GA · On-site

$117.80K - $155.30K/yr

You will work at the intersection of data engineering, machine learning operations, and edge AI ... Experience with edge AI deployment on NVIDIA Jetson or similar embedded GPU platforms. * Experience ...

h2o.ai

Senior Sales Engineer

Atlanta, GA · On-site

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS ... In this role, you'll combine deep technical expertise in Machine Learning and Generative AI with ...

h2o.ai

Senior Sales Engineer

Atlanta, GA · On-site

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS ... In this role, you'll combine deep technical expertise in Machine Learning and Generative AI with ...

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Freelance Nvidia Machine Learning information

What are the key skills and qualifications needed to thrive as a Freelance Nvidia Machine Learning Engineer, and why are they important?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

What are some common challenges freelance Nvidia Machine Learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What does a Freelance Nvidia Machine Learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.

What is the difference between Freelance Nvidia Machine Learning vs Freelance Data Scientist?

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are the most commonly searched types of Nvidia Machine Learning jobs in Georgia? The most popular types of Nvidia Machine Learning jobs in Georgia are:
What are popular job titles related to Freelance Nvidia Machine Learning jobs in Georgia? For Freelance Nvidia Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Freelance Nvidia Machine Learning jobs in Georgia look for? The top searched job categories for Freelance Nvidia Machine Learning jobs in Georgia are:
Freelance Nvidia Machine Learning jobs near you

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Posted 5 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.