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Junior Machine Learning Jobs in New York (NOW HIRING)

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Junior Machine Learning information

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
What are the most commonly searched types of Machine Learning jobs in New York? The most popular types of Machine Learning jobs in New York are:
What are popular job titles related to Junior Machine Learning jobs in New York? For Junior Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning jobs in New York look for? The top searched job categories for Junior Machine Learning jobs in New York are:
What cities in New York are hiring for Junior Machine Learning jobs? Cities in New York with the most Junior Machine Learning job openings:
Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Lead Machine Learning Scientist, New AI Products and Platforms

The New York Times

New York, NY • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday

Job description

About the Role, Mission or Department Overview

The New York Times is hiring a Lead Machine Learning Scientist to join the New A.I. Products & Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations.

You will provide technical leadership to a team of ML scientists developing embedding models and semantic retrieval algorithms to power new A.I. experiences across our products. Your work will allow teams across the company to build, deploy, and manage applications that use large language models to promote our journalism and our business. Your team will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role.

Responsibilities:

  • You will lead the design and training of embedding models for representation learning, for example using transformer encoders and Two Tower architectures.
  • You will lead the fine-tuning, adaptation, and evaluation of language models for custom product use cases and content enrichment, including information extraction from Times content at scale
  • You will productionalize embedding models and language models while working closely with engineering teams, to integrate ML and AI into user-facing products throughout The Times
  • You will help to define shared practices around evaluation, responsible A.I. use, and what "good" is inside an organization where judgment and independence are important
  • You will identify novel project opportunities to solve critical problems and act on those proposals
  • You will scope ongoing product improvements, prioritizing requests from your team
  • You will build and facilitate relationships across the organization to ensure you meet our projects' goals.
  • Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

  • PhD plus 4+ years experience, or 7+ years experience, in machine learning, statistics, computer science, computational social science, or another quantitative/computational discipline
  • 4+ years of experience in creatively reframing our challenges as Machine Learning tasks
  • 4+ years of experience with data cleaning, preparation, feature engineering, and model selection techniques
  • 2+ years of experience coding and deploying in production environments using Python, developing and deploying complex algorithms that are integrated into company process
  • 2+ years of experience building production systems that use LLMs, vision-language models, graph neural networks, or other deep learning models to solve user-facing problems
  • 1+ years of experience mentoring peers or junior ML scientists through pairing and algorithm, model, and code review

Preferred Qualifications:

  • PhD or Master's research experience in Applied AI
  • 1+ years of experience with information retrieval or search systems
  • 2+ years of experience collaborating cross-functionally with product managers and software engineers
  • 2+ years of experience scoping and staging work into well-defined milestones and delivering on communicated timelines

REQ-020336

Compensation and Benefits For This Role:

In addition to base salary, this role is also eligible for variable pay, such as an annual bonus and restricted stock. Benefits include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, employee stock purchase plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs. 

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