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Remote Deep Learning Jobs in New York (NOW HIRING)

Senior Machine Learning Engineer

New York, NY ยท Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... The ideal candidate will have deep expertise in Machine Learning and building generalizable ...

Senior Staff Machine Learning Engineer

New York, NY ยท On-site +1

$245K - $319K/yr

You will apply state-of-the-art techniques, including hybrid retrieval, multi-tasking deep learning ... This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ...

Experience with training and deploying NLP deep learning models * Exceptional skills in Python, SQL ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

Founded in 2017, OneTrack combines computer vision, deep learning, and low-cost edge sensors to ... PTO and Flexible working hours and remote work options * Opportunities for professional growth and ...

Modelling Resident (8-Month Contract)

New York, NY ยท On-site +1

$17.50 - $22.25/hr

Strong Python skills and experience with deep learning frameworks (PyTorch, JAX, or TensorFlow ... Strong communication and self-awareness - you know how to collaborate in a remote environment and ...

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Remote Deep Learning information

See New York salary details

$27

$62

$94

How much do remote deep learning jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for remote deep learning in New York is $62.48, according to ZipRecruiter salary data. Most workers in this role earn between $50.58 and $77.36 per hour, depending on experience, location, and employer.

What is a remote deep learning engineer?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What are common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

What is the difference between Remote Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

What skills and qualifications are needed to thrive as a remote deep learning engineer?

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.
What are the most commonly searched types of Deep Learning jobs in New York? The most popular types of Deep Learning jobs in New York are:
What cities in New York are hiring for Remote Deep Learning jobs? Cities in New York with the most Remote Deep Learning job openings:
Infographic showing various Remote Deep 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, with an average salary of $129,962 per year, or $62.5 per hour.

Machine Learning Engineer in NLP (Contract) - Remote

Cloudacio

Manhattan, NY โ€ข Remote

Contractor

Re-posted yesterday


Job description

About Cloudacio

Cloudacio stands at the forefront of cloud technology, pioneering advanced, AI-driven solutions to revolutionize how businesses leverage the cloud. Our core values revolve around relentless innovation, technical excellence, and a steadfast commitment to delivering cutting-edge cloud services. Embracing a remote and flexible work philosophy, we offer our team the freedom to collaborate and innovate from anywhere in the world.


Role Overview

As a Machine Learning Engineer specializing in Natural Language Processing (NLP) at Cloudacio, you will develop and refine advanced solutions in language understanding, text generation, and semantic analysis. Working with Large Language Models (LLMs) and the latest NLP technologies, your role will be pivotal in project success and delivering client-focused AI solutions. Proficiency in English is essential for effective communication with clients. Availability for scheduled client meetings and responsiveness on Slack during EST business hours is required.

Key Responsibilities
  • Develop and implement NLP solutions with a focus on LLMs and semantic analysis.
  • Attend client meetings, offering pre-sales support and NLP-focused technical insights.
  • Responsiveness via Slack during EST business hours.
  • Engage in client-facing roles, translating business needs into robust NLP solutions.
  • Collaborate with cross-functional teams to integrate NLP technologies into broader AI solutions.
  • Stay updated with the latest NLP developments, enhancing our offerings continuously. 


Core Skills & Technologies

  • NLP and LLM Expertise: Profound knowledge of NLP and transformer models including LLMs (e.g., GPT-4, Llama-2), RoBERTa, T5, ELECTRA, and BERT.
  • Deep Learning and Frameworks: Strong proficiency in TensorFlow and PyTorch for developing complex NLP models.
  • Data Handling: Skilled in data annotation and preprocessing for large NLP datasets.
  • Cloud Platforms: Familiarity with cloud environments like AWS, Azure, or GCP for deploying and managing NLP solutions.
  • Excellent English communication skills for client-facing roles and technical discussions.
  • Consulting Experience: Previous consulting or startup environment experience.
  • Entrepreneurial Spirit: Ability to independently handle customer interactions and lead projects.


What We Offer

  • Flexible work arrangements to accommodate project needs and personal preferences.
  • Growth potential in a dynamic environment focusing on AI and cloud technologies.
  • A culture that values innovation, communication, and proactive problem-solving.
  • Opportunity to work on innovative projects with significant real-world impact.
Employment Type: CONTRACTOR