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Remote Machine Learning Postdoc Jobs in New York

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Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

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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 are popular job titles related to Remote Machine Learning Postdoc jobs in New York?

For Remote Machine Learning Postdoc jobs in New York, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Postdoc jobs in New York look for?

The top searched job categories for Remote 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:

Remote Machine Learning Postdoc jobs near you
Infographic showing various Remote Machine Learning Postdoc job openings in New York as of September 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 100% Remote job distribution.

Machine Learning Engineer - Remote

New York, NY • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

Full-time

Posted 16 days ago

Job description

Machine Learning Engineer

Role Type: Contractor
Location: Remote

About the Role

We are looking for skilled Machine Learning Engineers to support AI training and evaluation projects. You'll use Python, machine learning, and data expertise to develop, evaluate, and improve ML solutions.

Key Responsibilities
  • Develop and refine machine learning models using Python.
  • Analyze and manage datasets using MongoDB.
  • Evaluate models, tune performance, and benchmark results.
  • Build data preprocessing and ML workflows.
  • Identify opportunities to improve model performance.
  • Document experiments, methodologies, and results.
Required Skills
  • Python
  • Machine Learning
  • MongoDB
  • Data Analysis & Preprocessing
  • Model Evaluation
  • Feature Engineering
Preferred Qualifications
  • Strong experience with Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
  • Hands-on MongoDB experience in ML or data projects.
  • Strong problem-solving and analytical skills.
  • Understanding of ML evaluation metrics and data modeling.
  • Experience deploying ML models in cloud or enterprise environments.
  • Strong technical documentation and communication skills.