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Machine Learning Analyst 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 ...

RIT Solutions

Machine Learning Engineer

Fremont, CA

Machine Learning Engineer Location: Fremont, CA Duration: 12+ Months Tesla/ $65 About the Role Our ... Integrate and analyze heterogeneous datasets, including image data, sensor outputs, voice ...

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 ...

LeanData

Machine Learning Engineer

Santa Clara, CA

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify ... Analyze findings from experiments and provide clear, actionable recommendations on optimal AI/ML ...

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How much do machine learning analyst jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning analyst in the United States is $73,261.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,500.00 and $87,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Analyst position, and why are they important?

To thrive as a Machine Learning Analyst, you need strong analytical skills, a solid grasp of statistics and programming languages such as Python or R, and typically a degree in computer science, mathematics, or a related field. Experience with machine learning frameworks like TensorFlow or scikit-learn, data visualization tools such as Tableau, and relevant certifications (e.g., Google Data Analytics) are often expected. Excellent problem-solving, collaboration, and communication abilities help you explain complex results and work effectively with cross-functional teams. Together, these skills ensure you can accurately interpret data, build robust models, and present actionable insights that drive organizational growth.

What is a Machine Learning Analyst job?

A Machine Learning Analyst is responsible for analyzing data, building models, and extracting insights using machine learning techniques. They work with large datasets, clean and preprocess data, and apply statistical methods to drive business decisions. Their role often involves collaborating with data scientists, engineers, and business teams to optimize predictive models. Strong programming skills in Python or R, knowledge of machine learning frameworks, and experience with data visualization are essential for this role.

What are typical projects or tasks a Machine Learning Analyst handles on a daily basis?

Machine Learning Analysts commonly work on tasks such as collecting, cleaning, and analyzing large datasets, developing predictive models, and interpreting results to generate actionable business insights. They may also collaborate closely with data engineers, software developers, and business stakeholders to translate business problems into data-driven solutions. Regular responsibilities include preparing data visualizations, running experiments to improve model performance, and documenting their findings for non-technical audiences. This hands-on work in a team-oriented environment ensures that their analyses directly contribute to key business decisions and continuous improvement.

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Machine Learning Analyst jobs near you
Machine Learning Engineer

Machine Learning Engineer

Dark Wolf Solutions

Herndon, VA • On-site

Full-time

Posted 24 days ago

Job description

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We're proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission's biggest challenges.
Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.
Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve specific business problems.
  • Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
  • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
  • Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
  • Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
  • Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
  • Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
  • Troubleshoot and resolve issues related to machine learning models and pipelines.
  • Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
  • Contribute to the development of best practices and standards for machine learning development and deployment within the team.
  • Document machine learning models, experiments, and deployment processes.
  • Potentially work with large datasets and big data technologies.
  • Optimize machine learning models for performance and efficiency.

Qualifications:
  • Master's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
  • Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
  • Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
  • Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).
  • Experience with data preprocessing, feature engineering, and data visualization techniques.
  • Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
  • Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
  • Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
  • Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.

Preferred Skills:
  • Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
  • Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
  • Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Experience with building and deploying RESTful APIs.
  • Familiarity with big data technologies and distributed computing.
  • Experience with statistical modeling and inference.

Position Clearance Requirement:
TS/SCI with Full-Scope Polygraph
This position is located in Chantilly/Herndon, VA.
We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

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