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Founding Machine Learning Engineer Jobs in Atlanta, GA

Senior Machine Learning Engineer

Atlanta, GA ยท Remote

$165K - $225K/yr

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 ...

Machine Learning Engineer

Atlanta, GA ยท On-site

$85.92 - $130/hr

* Senior MLOps Engineer (Contractor) About the Role: * Client is seeking an experienced Senior MLOps Engineer to join client's Data Science Enablement (MLOps) team as a contractor. * Candidates will be ...

... Machine Learning driven features with Python (including NumPy, SciPy, Pandas, TensorFlow, Pytorch) Other Qualifications: * Strong programming skills in Python with proficiency in relevant libraries ...

The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that models and decisioning systems are production-ready, observable, cost-efficient, and seamlessly ...

New

Machine Learning Engineer (Atlanta)

Atlanta, GA ยท On-site

$139K - $215K/yr

Our Atlanta-based client is seeking an experienced engineer to advance their AI capabilities. Using state-of-the-art sensor and data processing systems, you would lead your own team of high-caliber ...

Sr. Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will own critical production ML systems across ...

New

Showing results 41-60

Founding Machine Learning Engineer information

See Atlanta, GA salary details

$30.3K

$123.8K

$186.1K

How much do founding machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for founding machine learning engineer in Atlanta, GA is $123,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $149,100.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $120,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses are also common components of compensation, especially in startup environments where they play a significant role in total earnings.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What are the key skills and qualifications needed to thrive as a founding machine learning engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA โ€ข Remote

$165K - $225K/yr

Full-time

Re-posted 15 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.