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Machine Learning Analysis Jobs (NOW HIRING)

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Micron

Machine Learning Engineer

Boise, ID · On-site

Analyze existing Micron data sets to identify patterns, trends, and insights that can enhance machine learning model development. Design, implement, and iterate on machine learning models to address ...

SAIC

Machine Learning Developer

Arlington, VA · Hybrid

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ... Strong analytical and problem-solving skills. * Excellent communication and teamwork abilities.

Givzey

Machine Learning Engineer

Design, develop, and implement machine learning models and algorithms ... Analyze large datasets and extract meaningful insights * Collaborate with cross-functional teams to ...

SAIC

Machine Learning Developer

Arlington, VA · On-site

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ... Strong analytical and problem-solving skills. * Excellent communication and teamwork abilities.

Hang

Machine Learning Engineer

New York, NY · On-site +1

This person will implement and develop machine learning models to enhance our platform ... Analyze large datasets to identify trends and patterns, and use this information to inform model ...

Adobe

Machine Learning Engineer

San Jose, CA

Optimize machine learning models for performance and accuracy ... Analyze large datasets to extract meaningful insights and drive data-informed decisions * Engage in ...

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Machine Learning Analysis information

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How much do machine learning analysis jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for machine learning analysis in the United States is $39.52, according to ZipRecruiter salary data. Most workers in this role earn between $28.85 and $43.27 per hour, depending on experience, location, and employer.

What is the difference between Machine Learning Analysis vs Data Scientist?

AspectMachine Learning AnalysisData Scientist
Required CredentialsTypically a degree in computer science, statistics, or related fields; certifications in machine learning or data analysisSimilar credentials; often includes advanced degrees in data science, statistics, or related areas
Work EnvironmentPrimarily focused on developing, testing, and deploying machine learning models in tech companies, research labs, or analytics firmsBroader role involving data collection, cleaning, analysis, and communicating insights across various industries
Employer & Industry UsageUsed in tech, finance, healthcare, and e-commerce for predictive modeling and automationApplied across industries for strategic decision-making, data-driven insights, and business intelligence

While both roles require strong analytical skills and knowledge of programming, Machine Learning Analysis specializes in creating models that automate predictions, whereas Data Scientists focus on comprehensive data analysis and storytelling to inform business strategies.

What cities are hiring for Machine Learning Analysis jobs? Cities with the most Machine Learning Analysis job openings:

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA

Other

Posted 19 days ago

Job description

Who are we?

RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
The role?

We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.

What will you do?
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Analyze the impact of integrating new data sources and features into our models.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • Document experiments, assumptions, and outcomes; maintain reproducibility
What are we looking for?
  • Bachelor's degree in Mathematics, Physics, Computer Science, or a related technical field.
  • At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
Nice-to-Have
  • Familiarity with system programming languages including C++ and Rust is a plus.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.

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