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Machine Learning Developer Jobs (NOW HIRING)

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Honolulu, HI · On-site

Machine Learning Engineer LOCATION Honolulu, HI 96815 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Avride

Machine Learning Engineer

Austin, TX

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

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Machine Learning Developer information

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How much do machine learning developer jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for machine learning developer in the United States is $38.42, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $51.92 per hour, depending on experience, location, and employer.

What does a Machine Learning Developer do?

A Machine Learning Developer designs, builds, and implements machine learning models and systems that enable computers to learn from data without explicit programming. They work with large datasets, select appropriate algorithms, and optimize models for various tasks such as predictions, classifications, and recommendations. Their responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models into production environments. Machine Learning Developers typically collaborate with data scientists, software engineers, and business teams to deliver AI-powered solutions.

Is ML a high paying job?

Machine Learning Developer roles are generally well-paid due to the specialized skills required, such as programming in Python or R and knowledge of algorithms and data analysis. Salaries tend to be higher than average in tech hubs and increase with experience, certifications, and expertise in tools like TensorFlow or PyTorch.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior machine learning engineers or AI research directors, often found in large tech companies or specialized firms. These positions usually require advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership. Compensation at this level reflects significant expertise, responsibility, and impact within the organization.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and system integration. While AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Continuous learning and expertise in programming, data analysis, and model optimization remain critical for MLEs' roles.

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

AspectMachine Learning DeveloperData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications like TensorFlow or AWS MLBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops and deploys ML models in software or cloud environmentsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, predictive modeling, and insights

Both roles require strong programming skills and knowledge of ML algorithms. Machine Learning Developers focus on building and deploying models in production environments, while Data Scientists analyze data to inform business decisions. The roles often overlap but differ mainly in their primary focus and end goals.

What engineer makes $500,000 a year?

Senior machine learning developers or AI engineers with extensive experience, advanced skills in deep learning, and expertise in tools like TensorFlow or PyTorch can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such roles often require advanced degrees, certifications, and a strong track record of successful projects.

What are some common challenges faced by Machine Learning Developers when deploying models to production environments?

Machine Learning Developers often encounter challenges such as ensuring model scalability, managing data drift, and integrating models with existing systems during deployment. Another frequent hurdle is monitoring model performance in real time and retraining models as new data becomes available. Collaborating closely with data engineers, DevOps, and software developers is essential to streamline the deployment pipeline and maintain model reliability in production.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer, and why are they important?

To excel as a Machine Learning Developer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or related fields. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, as are certifications in data science or AI. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data findings into actionable solutions. These skills and qualities are essential to develop accurate models, collaborate with stakeholders, and drive innovation in a rapidly evolving field.
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What are the most commonly searched types of Machine Learning Developer jobs? The most popular types of Machine Learning Developer jobs are:
What states have the most Machine Learning Developer jobs? States with the most job openings for Machine Learning Developer jobs include:
What job categories do people searching Machine Learning Developer jobs look for? The top searched job categories for Machine Learning Developer jobs are:
Machine Learning Developer jobs near you
Infographic showing various Machine Learning Developer job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $79,911 per year, or $38.4 per hour.

Machine Learning Engineer

Quanta Search

Manhattan, NY • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Our client is a process driven investment management group consisting of a team of researchers, traders and technologists who harness and apply the power of technology and automation to identify, model and trade global financial markets. Thisdivision offers an array of quantitative investment fund products to its clients.
They are seeking candidates with exceptional academic credentials to join theirteam and participate in and support of the firm's efforts in the research, trading and production processes.
They look for candidates who are eager to make an impact by doing real, hands-on research and development. Candidates must possess exceptional knowledge of mathematical and statistical methods as well as a proven ability to solve complex problems. A desire to work with large data sets and apply creative thinking is required. Successful candidates will also have deep interest in learning about trading and the financial markets.
They offera supportive environment that fosters independent thought in a collegial, results oriented, work setting. Researchers and developers there are passionate about their work, model building, data and technology.
You are curious and intellectually driven to succeed. You'll beprovidedwith the tools, resources and training required to satisfy that curiosity and passion, leading them to new insights and discoveries. Theirprocess driven approach enables these insights to be thoroughly tested in a systematic fashion and ultimately, if confirmed, integrated into theportfolio.
Role:
Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud computing. Machine Learning Engineers should be comfortable with data engineering and should have an interest in the data science.
What they will do:
They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Minimum Requirements:
  • Strong understanding of statistical analysis and computational modelling.
  • Strong understanding of algorithms and data structures.
  • Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
  • TensorFlow (or another GPU integrated deep learning library).
  • Deep understanding of machine learning algorithms.
  • Deep understanding of numerical optimization.
  • Strong understanding of data structures and algorithms.
Plus, but not required:
  • Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
  • Experience building industrial grade ETL pipelines.
  • Experience building frontend systems.
  • Familiarity with dashboards and other visualization tools.
  • Ability to derive generalization bounds for common ML algorithms.
  • Experience developing new machine learning algorithms.

Apply