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Weekend No Experience Machine Learning Jobs in New York

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to ...

Master's degree in Computer Science, Engineering, Information Systems, or related field. * 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras ...

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 ...

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 ...

Proven experience as a Machine Learning Engineer or similar role * Understanding of data structures, data modelling and software architecture * Deep knowledge of math, probability, statistics and ...

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

Preferred Qualifications: • Master's degree in Computer Science, Engineering, Information Systems, or related field. • 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow ...

Minimum of 2 years of experience in a data science role. Proficiency in programming languages such as Python or R.. Strong understanding of machine learning techniques and algorithms. Preferred ...

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 ...

Experience with sequential modeling and time series forecasting using deep learning * Experience ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

Experience with sequential modeling and time series forecasting using deep learning * Experience ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

... Machine Learning Researcher while also providing a truly unparalleled educational experience ... You'll work side by side with experienced ML Researchers on projects that we've selected for their ...

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Weekend No Experience Machine Learning information

What is a weekend no experience machine learning job?

A Weekend No Experience Machine Learning job is a part-time opportunity typically scheduled on weekends for individuals interested in machine learning but who have little or no prior experience in the field. These jobs are designed for beginners and may involve tasks such as data labeling, assisting with simple coding projects, or supporting research teams. They provide a great entry point for those looking to gain hands-on experience, learn industry tools, and build their resumes while balancing other commitments like school or a full-time job.

What are the key skills and qualifications needed to thrive as a weekend no experience machine learning professional?

To thrive as a Machine Learning professional, foundational knowledge in mathematics, statistics, and programming (especially Python) is essential, typically demonstrated through coursework or self-directed learning. Familiarity with machine learning libraries such as scikit-learn or TensorFlow and version control systems like Git is highly beneficial, even at an entry level. Curiosity, problem-solving abilities, and effective communication help newcomers stand out as they learn quickly and collaborate with more experienced team members. These skills and qualities are crucial to building practical expertise, contributing to projects, and adapting to the evolving demands of machine learning roles.

What kind of support and training can I expect starting a weekend no experience machine learning role?

In a weekend machine learning role designed for beginners, you can typically expect onboarding sessions, access to online learning materials, and mentorship from more experienced team members. Many organizations provide structured guidance through tutorials, code reviews, and collaborative projects to help you build foundational skills. You’ll likely be assigned manageable tasks that allow you to gradually familiarize yourself with real datasets and tools, while regular feedback ensures your steady progress. Team meetings and open communication channels are common, so don’t hesitate to ask questions and seek help as you learn.

What is the difference between Weekend No Experience Machine Learning vs Weekend Data Analyst?

AspectWeekend No Experience Machine LearningWeekend Data Analyst
Required CredentialsBasic understanding of programming, no formal certification neededBasic knowledge of data analysis tools, possibly some certifications
Work EnvironmentProject-based, flexible hours, often remotePart-time, flexible hours, often remote or on-site
Industry UsageTech, finance, healthcare, startupsBusiness, marketing, finance, consulting

Weekend No Experience Machine Learning roles focus on introductory tasks like data preprocessing and basic model training, suitable for beginners. Weekend Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making. Both roles are flexible and often part-time, but they differ in technical depth and industry focus.

What are popular job titles related to Weekend No Experience Machine Learning jobs in New York?

For Weekend No Experience Machine Learning jobs in New York, the most frequently searched job titles are:

What job categories do people searching Weekend No Experience Machine Learning jobs in New York look for?

The top searched job categories for Weekend No Experience Machine Learning jobs in New York are:

What cities in New York are hiring for Weekend No Experience Machine Learning jobs?

Cities in New York with the most Weekend No Experience Machine Learning job openings:

Full-time

Posted 2 days ago

New


Job description


Join Cantor Fitzgerald Technology Markets LLC as a Machine Learning Engineer focused on building AI-driven solutions for a high-volume financial services business. You will work closely with product, engineering, and business teams to create, test, and operationalize large language model (LLM) applications, ensuring they meet performance, reliability, and responsible-AI standards.
Responsibilities
  • Design and implement LLM-driven features in production systems.
  • Build and maintain data pipelines for both structured and unstructured data.
  • Write clean, testable Python code and maintain reusable libraries.
  • Develop prompts, tool-calling workflows, and retrieval pipelines.
  • Create evaluation suites, define success metrics, and analyze failures.
  • Diagnose and mitigate hallucination, latency, and cost issues.
  • Collaborate with product, engineering, and business stakeholders.
  • Implement monitoring, logging, and alerting for AI services.
  • Contribute to responsible-AI guardrails and human-in-the-loop processes.
  • Document designs, experiments, and findings for internal knowledge sharing.

Qualifications
  • Bachelor's degree in computer science, machine learning, mathematics, physics, statistics, econometrics, or equivalent practical experience.
  • Experience contributing to production or production-like software through work, internships, research, open source, or substantial personal projects.
  • Strong programming ability in Python with clear, tested, and maintainable code.
  • Experience with web services, data integrations, testing, logging, and basic monitoring across diverse data types.
  • Hands-on experience building with LLM tools or frameworks (prompting, structured outputs, tool-calling, retrieval, multi-step workflows) and awareness of common failure modes.
  • Experience evaluating LLM-powered applications: building test sets, reviewing failures, defining metrics, and iterating on prompts or retrieval.
  • Solid grounding in machine learning, statistics, and experimental design with ability to interpret technical papers and documentation.
  • Strong communication skills and comfort working with product, engineering, and business partners.
  • Interest in applying AI responsibly in financial services, including privacy, security, human review, and appropriate automation.
  • Familiarity with cloud deployment, containers, and modern release pipelines.

$140,000 - $160,000