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Work From Home Senior Machine Learning Engineer Jobs in Northfield, IL

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

This innovation supports the critical evolution from research applications to clinical deployment ... Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and ...

Career Renew

Senior ML Engineer

Chicago, IL · Remote

$180K - $240K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... backing from day one. * Work on genuinely cutting-edge AI problems -- low latency inference ...

TEKsystems

Machine Learning Engineer

Chicago, IL · On-site +1

$95 - $105/hr

Description Supplier Call notes Sr. ML Engineer - AI Space Posting new . Additional Role - Same ... Ideal Profile - Looking for candidates from strong technology companies. - Example profile ...

TEKsystems

Machine Learning Engineer

Chicago, IL · Remote

$95 - $105/hr

... from an engineering perspective. - Will be using existing models to create software services, not ... work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is ...

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Work From Home Senior Machine Learning Engineer information

See Northfield, IL salary details

$61.8K

$131.4K

$190.5K

How much do work from home senior machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for work from home senior machine learning engineer in Northfield, IL is $131,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $149,000.00 per year, depending on experience, location, and employer.

What is the difference between Work From Home Senior Machine Learning Engineer vs Data Scientist?

AspectWork From Home Senior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, tech-focusedRemote or on-site, research and analysis-driven
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, healthcare
Common Search IntentComparing remote ML engineering rolesUnderstanding data analysis roles

While both roles often work remotely and require strong technical backgrounds, a Senior Machine Learning Engineer focuses on developing and deploying ML models, whereas a Data Scientist emphasizes data analysis and insights. The roles overlap in credentials and industry usage but differ in daily responsibilities and project focus.

What cities near Northfield, IL are hiring for Work From Home Senior Machine Learning Engineer jobs?

Cities near Northfield, IL with the most Work From Home Senior Machine Learning Engineer job openings:

Work From Home Senior Machine Learning Engineer jobs near you
Infographic showing various Work From Home Senior Machine Learning Engineer job openings in Northfield, IL as of June 2026, with employment types broken down into 74% Full Time, 25% Part Time, and 1% Contract. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution, with an average salary of $131,381 per year, or $63.2 per hour.

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Re-posted 28 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.