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Remote Machine Learning Postdoc Jobs in New York

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

Showing results 21-40

Remote Machine Learning Postdoc information

What is a remote machine learning postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are the key skills and qualifications needed to thrive as a remote machine learning postdoc?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.

What are the most commonly searched types of Machine Learning Postdoc jobs in New York?

The most popular types of Machine Learning Postdoc jobs in New York are:

What cities in New York are hiring for Remote Machine Learning Postdoc jobs?

Cities in New York with the most Remote Machine Learning Postdoc job openings:

Infographic showing various Remote Machine Learning Postdoc job openings in New York as of August 2026, with employment types broken down into 5% Internship, 60% Full Time, 9% Part Time, and 26% Contract. Highlights an 100% Remote job distribution.

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 12 days ago


Job description

About the Role, Mission or Department Overview

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

Responsibilities:

  • You will design and train embedding models for representation learning, for example using transformer encoders and Two Tower architectures.
  • You will fine-tune and evaluate language models for custom use cases and content enrichment.
  • You will contribute to shared practices around evaluation, responsible A.I. use, and what "good" is inside an organization where judgment and independence are important
  • You will implement and deploy machine learning and AI research with robustness and reproducibility, with consideration of risks and trade-offs
  • You will adapt or develop ML and AI algorithms in cases when existing techniques are insufficient, while implementing simple approaches
  • You will communicate complex ideas in machine learning and AI while collaborating with all kinds of colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups
  • 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, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline
  • 2+ years experience with open source machine learning or statistical analysis tools
  • 2+ years coding experience in Python
  • 2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis
  • 1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow

Preferred Qualifications:

  • PhD or Master's research experience in Applied AI
  • 1+ years of experience with information retrieval or search systems
  • 1+ years of experience translating ambiguous business questions into machine learning problems
  • 1+ years of experience building data products, either internal or consumer-facing

REQ-020337

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.