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Apprentice Machine Learning Testing Jobs in New York, NY

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

We are looking for an outstanding machine learning engineer to join our team! The role will provide ... Experience with unit, integration, and load testing * Experience building APIs * Experience with ...

WireScreen

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

End-to-end machine learning model experience in production; that you've stood up a service including experimenting, training, testing and tuning a job against a dataset all the way through to ...

Prudential

Lead, Machine Learning Engineer

Newark, NJ · On-site

$107K - $141K/yr

Solve complex problems by writing and testing application code, developing and validating ML models ... Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression ...

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Solve complex problems by writing and testing application code, developing and validating ML models ...

Warnerbros

Machine Learning Engineer I

New York, NY · On-site

$106K - $146K/yr

CNN is seeking a Machine Learning Engineer I to build and deploy ML systems that power ... Implement rigorous experimentation and A/B testing frameworks to validate model performance and ...

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Solve complex problems by writing and testing application code, developing and validating ML models ...

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All JobsApprentice Machine Learning Testing JobsApprentice Machine Learning Testing Jobs in New York, NY

Apprentice Machine Learning Testing information

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How much do apprentice machine learning testing jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for apprentice machine learning testing in New York, NY is $21.18, according to ZipRecruiter salary data. Most workers in this role earn between $17.88 and $23.12 per hour, depending on experience, location, and employer.

What does an apprentice machine learning testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What kinds of projects or tasks can I expect to work on as an apprentice machine learning testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What are the key skills and qualifications needed to thrive as an apprentice machine learning testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are the most commonly searched types of Machine Learning Testing jobs in New York, NY?

The most popular types of Machine Learning Testing jobs in New York, NY are:

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Apprentice Machine Learning Testing jobs near you

Senior Machine Learning Engineer - Personalization

5014 Disney Entertainment & Sports LLC

Manhattan, NY • On-site

$148.70 - $199.40/hr

Other

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

Job description

Overview

Senior Machine Learning Engineer – Personalization

Location: On‑site, 4 days in‑person at designated office location.

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across our Disney Streaming suite, notably Disney+ and Hulu. We use a strong product mindset and focus on usability, ensuring every ML‑driven product enhances how users discover, interact, and enjoy our experiences. I am a member of this team and collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals.

As an Individual Contributor, you will lead recommendation and personalization algorithm research, development, and productionization for product areas, and coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. You will also help set the roadmap for algorithmic work.

Responsibilities
  • Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and explain methodologies to technical and non‑technical teams.
  • Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte‑scale datasets.
  • Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards.
  • Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve data collection, experimentation, and analysis.
Qualifications
  • Basic Qualifications:
  • 5+ years of experience developing machine learning models, large‑scale data analysis, and/or data engineering.
  • 5+ years of writing production‑level, scalable code (Python, SQL).
  • 3+ years of experience developing algorithms for deployment to production systems.
  • Deep understanding of modern machine learning (e.g., deep learning methods) and their mathematical underpinnings.
  • Experience deploying and maintaining pipelines and engineering big‑data solutions using Databricks, S3, and Spark.
  • Ability to gauge complexity and execute simple approaches for quick, effective solutions as appropriate.
  • Strong written and verbal communication skills.
  • Preferred Qualifications:
  • MS or PhD in statistics, math, computer science, or related quantitative field.
  • Production experience with developing content recommendation algorithms at scale.
  • Experience building and deploying full‑stack ML pipelines (data extraction, mining, model training, feature development, testing, deployment).
  • Familiar with metadata management, data lineage, and principles of data governance.
  • Experience loading and querying cloud‑hosted databases.
  • Experience with AWS and Databricks.
  • Required Education: Bachelor’s Degree in Computer Science, Math, Statistics, or a related quantitative field.
Benefits

Compensation includes an annual base salary in the range $148,700 – $199,400 (NY) or $141,900 – $190,300 (CA). The base pay is based on equity, geographic region, and experience. A bonus and/or long‑term incentive units may be provided, and you will receive a full range of medical, financial, and other benefits.

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