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Temporary Machine Learning Trainer Jobs in New York

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... An undergraduate or PhD student with practical experience training an ML model, working on an ML ...

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... An undergraduate or PhD student with practical experience training an ML model, working on an ML ...

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days ... with ML model training within cloud infra such as Azure, AWS, GCP Proven track record of ...

... for training and using MCP agents to streamline research workflow. Requirements: * PhD or PhD ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

... for training and using MCP agents to streamline research workflow. Requirements: * PhD or PhD ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

They are seeking a Machine Learning Engineer focused on MLOps to operationalize and scale their ... training pipelines • Improve data processing, annotation workflows, and ML system efficiency • ...

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... Experience building and maintaining training and inference infrastructure, with an understanding of ...

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... Experience building and maintaining training and inference infrastructure, with an understanding of ...

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... Diagnose and resolve performance issues across training pipelines: data loading throughput, storage ...

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... Diagnose and resolve performance issues across training pipelines: data loading throughput, storage ...

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... for training models, and how to reason about performance. We're looking for someone who: * Is a ...

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... for training models, and how to reason about performance. We're looking for someone who: * Is a ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Summit, NJ · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Hoboken, NJ · Remote

$18 - $40/hr

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Temporary Machine Learning Trainer information

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

To thrive as a Temporary Machine Learning Trainer, you need a solid background in machine learning concepts, data analysis, and model evaluation, usually supported by a relevant degree or experience in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or scikit-learn), and educational tools is typically required. Strong communication, adaptability, and instructional skills help trainers effectively convey complex topics and respond to diverse learner needs. These skills ensure trainees gain practical knowledge and confidence, contributing to successful training outcomes and organizational goals.

What are some common challenges faced by Temporary Machine Learning Trainers, and how can they be managed effectively?

Temporary Machine Learning Trainers often face the challenge of quickly adapting to new team environments and rapidly understanding existing workflows. Additionally, they may need to balance delivering training sessions with handling updates to curriculum or technology. Effective communication with permanent staff and staying up-to-date with the latest machine learning tools can help manage these challenges. Being proactive in seeking feedback and clarifying expectations early on can also contribute to a smoother transition and more impactful training sessions.

What is the difference between Temporary Machine Learning Trainer vs Data Scientist?

AspectTemporary Machine Learning TrainerData Scientist
CredentialsRelevant certifications (e.g., AWS, Google Cloud), technical trainingAdvanced degrees (Master's or PhD) in data science, statistics, or related fields
Work EnvironmentTraining sessions, workshops, corporate training settingsData analysis, modeling, research environments, often in offices or labs
Employer & Industry UsageTech companies, educational institutions, consulting firmsTech, finance, healthcare, research organizations

While both roles involve working with data and machine learning, a Temporary Machine Learning Trainer primarily focuses on educating and training teams or clients on machine learning tools and concepts. In contrast, a Data Scientist develops models, analyzes data, and derives insights for decision-making. The roles differ mainly in their focus—training versus data analysis—though they share foundational technical skills.

What are Temporary Machine Learning Trainers?

Temporary Machine Learning Trainers are professionals hired on a short-term or contract basis to develop, implement, and refine machine learning models or to train teams in machine learning techniques. Their responsibilities often include preparing training data, selecting appropriate algorithms, and ensuring models are accurate and efficient. They may also provide guidance to organizations on best practices and help upskill employees in machine learning concepts. These roles are typically project-based and may last from a few weeks to several months, depending on organizational needs.
What cities in New York are hiring for Temporary Machine Learning Trainer jobs? Cities in New York with the most Temporary Machine Learning Trainer job openings:
Infographic showing various Temporary Machine Learning Trainer job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Jane Street

New York, NY • On-site

Full-time

Re-posted 7 days ago


Job description

About the Position
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.
Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you'd like to learn more, you can have a look at our Machine Learning page.
During the program, you'll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we're still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including 1-2 dedicated to assessing ML engineering skills.
Learn more about Jane Street's internship program here.
About You
If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in. We don't expect you to have a background in finance-we're more interested in how you think and learn than what you currently know. You should be:
  • An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow
  • A top-notch programmer with a love for technology
  • Intellectually curious, collaborative, and eager to learn
  • Humble and unafraid to ask questions and admit mistakes