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Apprentice Machine Learning Testing Jobs in New York

DraftKings

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Build rigorous testing and statistical validation frameworks to measure model performance and ... Champion machine learning best practices, including responsible and ethical AI development ...

Teleskope

Machine Learning Engineer

New York, NY · On-site

$160K - $210K/yr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification ... Implement evaluation, monitoring, and regression testing frameworks in collaboration with QC. * ...

PhysicsX

Machine Learning Engineer

New York, NY · On-site

... testing, CI/CD, API design, MLOps) * Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) * Distributed computing frameworks (e.g ...

Button

Senior Machine Learning Engineer

Manhattan, NY

$153K - $198K/yr

Senior Machine Learning Engineer Button's mission is to empower the companies shaping the creator ... Write clear, maintainable code with strong software engineering practices including testing ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

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

Capital One

Lead Machine Learning Engineer

New York, NY · On-site

$112K - $147K/yr

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

Phia

Senior Machine Learning Engineer

New York, NY · On-site

$185K - $265K/yr

Overview As a Senior Machine Learning Engineer at Phia, you'll build and scale production ML ... Solid understanding of experiment design and causal inference, including A/B testing and offline ...

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Apprentice Machine Learning Testing information

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 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 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 popular job titles related to Apprentice Machine Learning Testing jobs in New York? For Apprentice Machine Learning Testing jobs in New York, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in New York look for? The top searched job categories for Apprentice Machine Learning Testing jobs in New York are:
What cities in New York are hiring for Apprentice Machine Learning Testing jobs? Cities in New York with the most Apprentice Machine Learning Testing job openings:
Apprentice Machine Learning Testing jobs near you

Associate, Machine Learning Engineer

Cantor Fitzgerald Securities

Manhattan, NY • On-site

Full-time

Posted 3 days ago

Job description

We are seeking an early-career engineer to join our team and play a vital role in developing and enhancing AI-powered applications for our financial services business. The ideal candidate will have a solid foundation in software development, hands-on experience with modern AI tools, and a keen interest in understanding the behavior of language models in real-world applications. As an Associate, you will have the opportunity to work closely with our experienced engineers and contribute to the growth and success of our innovative AI initiatives.
Company overview: 

Built upon the foundation of innovative technology and exceptional talent, BGC is a pioneering global brokerage and financial technology company servicing the financial markets. We are agile and dynamic in our approach, delivering world-class products to our diverse customer base daily. Our Financial Services business provides a full range of trade execution and broker-dealer services. 

The benefit of BGC's integrated platform is that it gives customers flexibility and choice in price discovery, execution, and processing of their transactions, through voice, hybrid, or fully electronic brokerage options. In addition, our BGC Trader and BGC Market Data platforms offer financial technology solutions, market data and analytics related to financial instruments and markets.

Agency Notice:

BGC Group & affiliates do not accept agency resumes. Please do not forward resumes to our job alias, employees or any other company location. BGC Group & affiliates are not responsible for any fees related to unsolicited resumes. Please contact the Recruitment function for additional details. 
  • Bachelor's degree in a technical field (computer science, machine learning, mathematics, etc.) or equivalent practical experience.
  • Experience contributing to production-level software development, internships, research, or substantial personal projects.
  • Strong programming skills in Python, with a focus on writing clear, tested, and maintainable code.
  • Hands-on experience with web services, data integration, testing, logging, and monitoring.
  • Practical knowledge of building with LLMs and understanding common failure modes.
  • Ability to test, evaluate, and improve LLM-powered applications.
  • Grounding in machine learning, statistics, and experimental design, with a knack for technical documentation.
  • Excellent communication skills and a collaborative mindset.
  • Interest in applying AI responsibly in financial services.
  • Familiarity with agentic workflows, evaluation tools, and cloud deployment is a plus.

Compensation

  • Collaborate with a cross-functional team to build, evaluate, and improve AI-powered financial services applications.
  • Design and implement machine learning models and algorithms to solve complex business problems.
  • Work with large language models (LLMs) and understand their behavior and potential failure modes.
  • Conduct testing and evaluation of LLM-powered applications, analyzing failures and defining success metrics.
  • Apply machine learning, statistics, and experimental design principles to reason about model behavior.
  • Communicate effectively with product, engineering, and business partners to align on project goals.
  • Ensure responsible AI practices are followed, considering privacy, security, and appropriate automation.
  • Stay updated with the latest advancements in AI and machine learning technologies.
  • Document and present project progress and findings to stakeholders.
  • Provide support and mentorship to junior team members as needed.

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