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Entry Level Google Cloud Machine Learning Engineer Jobs

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Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks ... Microsoft Azure cloud platform * DevOps and/or MLOps practices * Model development, deployment ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

Description: Paylocity is an award-winning provider of cloud-based HR and payroll software ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

Paylocity

Machine Learning Engineer

Job Type Full-time Description Paylocity is an award-winning provider of cloud-based HR and payroll ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

NICE Systems

Senior Machine Learning Engineer

Sandy, UT · On-site

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech ... Experience with cloud-based infrastructure (AWS, Azure, or Google Cloud Platform). * Ability to ...

NICE

Senior Machine Learning Engineer

Sandy, UT · Hybrid

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech ... Familiarity with multi-cloud deployment across AWS, Azure, and Google Cloud. * Experience with ...

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How much do entry level google cloud machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for entry level google cloud machine learning engineer in the United States is $69,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $78,500.00 per year, depending on experience, location, and employer.
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Entry Level Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Entry Level Google Cloud Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $69,362 per year, or $33.3 per hour.

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
CaseGuard is seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join their team. The role involves developing and deploying machine learning models focused on image and video processing, collaborating with cross-functional teams to design and optimize vision-based AI solutions.
Responsibilities:
• Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
• Optimize and fine-tune deep learning algorithms for real-time performance.
• Work closely with the software engineers and product teams to identify opportunities for leveraging data.
• Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
• Evaluate and optimize machine learning models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance to ensure reliability.
• Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
• Document processes, models, and implementations to ensure reproducibility and scalability.
Qualifications:
Required:
• Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
• Experience with data manipulation tools such as Pandas, NumPy, and SQL.
• Strong programming skills in Python and C++.
• Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
• Proficiency in working with image and video data, including preprocessing and augmentation techniques.
• Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
• Strong communication skills and the ability to work collaboratively in a team environment.
Preferred:
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems such as Git.
• Understanding software engineering best practices, including code review, testing, and documentation.
• Experience with Large Language Models (LLMs) is a great plus.
• Experience with data annotation tools and processes.
Company:
CaseGuard is a management solutions company. Founded in , the company is headquartered in Sterling, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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