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Entry Level Remote Machine Learning Jobs in Lake Hughes, CA

YO AI Labs

Senior Software Engineer - Remote

Los Angeles, CA · Remote

$132K - $174K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

YO AI Labs

Java Open Source Contributor

Los Angeles, CA · Remote

$55 - $71/hr

Remote Scope of Work: * Contribute production-quality code, reviews, and documentation to open ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Globe Life Insurance

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Entry Level Customer Sales Representative (100% Remote)

Los Angeles, CA · Remote

$60K - $80K/yr

Entry Level Customer Sales Representative (100% Remote) Remote | United States & Canada ... Learning about each client's needs and answering their questions * Explaining available benefit ...

Globe Life Insurance

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Entry Level Customer Sales Representative (100% Remote)

Los Angeles, CA · Remote

$60K - $80K/yr

Entry Level Customer Sales Representative (100% Remote) Remote | United States & Canada ... Learning about each client's needs and answering their questions * Explaining available benefit ...

Globe Life Insurance

Be Seen First

Entry Level Customer Sales Representative (100% Remote)

Los Angeles, CA · Remote

$60K - $80K/yr

Entry Level Customer Sales Representative (100% Remote) Remote | United States & Canada ... Learning about each client's needs and answering their questions * Explaining available benefit ...

Globe Life

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Entry Level- Sales Manager | 100% Remote

Los Angeles, CA · Remote

$60K - $79K/yr

As an Entry Level Sales Manager , your goal is to maintain the organization's relationships with ... Support for continuous learning and skill development. * Clear career paths with real internal ...

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Entry Level Remote Machine Learning information

See Lake Hughes, CA salary details

$12

$18

$22

How much do entry level remote machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for entry level remote machine learning in Lake Hughes, CA is $18.03, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $19.62 per hour, depending on experience, location, and employer.

How to get into entry level remote machine learning with no experience?

To start an entry-level remote machine learning role with no experience, focus on building foundational skills in programming languages like Python, learn key concepts such as data preprocessing and model training, and complete online courses or certifications in machine learning. Gaining practical experience through personal projects, participating in competitions, and creating a portfolio can also improve your chances of landing an entry-level position.

What is the difference between Entry Level Remote Machine Learning vs Entry Level Remote Data Science?

AspectEntry Level Remote Machine LearningEntry Level Remote Data Science
Required CredentialsBachelor's in CS, Math, or related; familiarity with ML frameworksBachelor's in CS, Statistics, or related; knowledge of data analysis tools
Work EnvironmentRemote, collaborative teams, coding-focusedRemote, data analysis, reporting, and visualization tasks
Industry UsageTech, AI startups, research institutionsFinance, healthcare, marketing, tech
Common Search/ComparisonYesYes

Entry Level Remote Machine Learning roles focus on developing algorithms and models using programming skills, while Entry Level Remote Data Science positions emphasize analyzing data, creating reports, and deriving insights. Both roles often require similar educational backgrounds and are common in tech-driven industries, but they differ in daily tasks and focus areas.

What job categories do people searching Entry Level Remote Machine Learning jobs in Lake Hughes, CA look for?

The top searched job categories for Entry Level Remote Machine Learning jobs in Lake Hughes, CA are:

What cities near Lake Hughes, CA are hiring for Entry Level Remote Machine Learning jobs?

Cities near Lake Hughes, CA with the most Entry Level Remote Machine Learning job openings:

Entry Level Remote Machine Learning jobs near you
Infographic showing various Entry Level Remote Machine Learning job openings in Lake Hughes, CA as of August 2026, with employment types broken down into 6% Internship, 66% Full Time, 15% Part Time, and 13% Contract. Highlights an 100% Remote job distribution, with an average salary of $37,501 per year, or $18 per hour.

Senior Machine Learning Engineer

Career Renew

Los Angeles, CA • Remote

$165K - $225K/yr

Full-time

Re-posted 21 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.