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Startup Machine Learning Remote Jobs in Georgia (NOW HIRING)

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... startup environment Extensive use of AI tools for coding, optimization, and ideation Preferred ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Adidev Technologies Inc

ML/AI Engineers

Atlanta, GA · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...

Adidev Technologies Inc

ML/AI Engineer

Alpharetta, GA · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects ...

Deckers

United States (Remote) Interested applicants must reside in one of the following approved states ... Enable future machine learning use cases by ensuring curated datasets are ML-ready, including ...

Airspace

Senior Specialist, Procurement

Atlanta, GA · On-site +1

As a recognized leader in AI and machine learning, our team leverages data and patented technology ... Airspace has been rated one of America's best Startup Employers, listed as one of CNBC's Disruptor ...

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Startup Machine Learning Remote information

What are the key skills and qualifications needed to thrive as a Startup Machine Learning Engineer in a remote setting, and why are they important?

To thrive as a Startup Machine Learning Engineer remotely, you need a solid background in computer science, statistics, and machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms (AWS, GCP, or Azure), and version control systems like Git is essential. Strong self-motivation, communication skills, and the ability to collaborate effectively across time zones help set outstanding candidates apart. These skills and qualities are crucial for delivering impactful ML solutions independently while contributing to fast-paced, distributed startup teams.

What are remote startup machine learning jobs?

Remote startup machine learning jobs involve working for early-stage companies or startups to design, develop, and implement machine learning models and solutions, all while working from a remote location. These roles typically require strong programming skills, experience with data analysis, and familiarity with machine learning frameworks. Startups often offer dynamic environments where employees can work on diverse projects and contribute directly to the product's growth. Remote positions provide flexibility in work location and hours, but also require self-motivation and excellent communication skills to collaborate with distributed teams.

What are some unique challenges faced by machine learning professionals working remotely at a startup?

Machine learning professionals at startups often encounter fast-paced environments where priorities can shift quickly, and working remotely adds another layer of complexity. Collaboration with cross-functional teams, such as engineers and product managers, may require proactive communication to ensure alignment and clarity on project goals. Additionally, limited resources and data infrastructure at startups may mean you'll need to wear multiple hats and help shape processes from the ground up. However, this environment offers high autonomy, opportunities to have a direct impact, and rapid career growth potential as the startup scales.
What are popular job titles related to Startup Machine Learning Remote jobs in Georgia? For Startup Machine Learning Remote jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Startup Machine Learning Remote jobs in Georgia look for? The top searched job categories for Startup Machine Learning Remote jobs in Georgia are:
What cities in Georgia are hiring for Startup Machine Learning Remote jobs? Cities in Georgia with the most Startup Machine Learning Remote job openings:
Startup Machine Learning Remote jobs near you

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted 20 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.