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Remote Data Scientist Deep Learning Jobs in Jupiter, FL

ServiceNow

Senior Staff Database Engineer

West Palm Beach, FL · On-site +1

$102K - $139K/yr

Our ServiceNow AI platform brings together any AI, any data, and any workflow- helping 85% of the ... We are looking for a strong database engineer with deep technical expertise, sharp logical ...

ServiceNow

Senior Staff Database Engineer

West Palm Beach, FL · On-site +1

$102K - $139K/yr

Our ServiceNow AI platform brings together any AI, any data, and any workflow-- helping 85% of the ... We are looking for a strong database engineer with deep technical expertise, sharp logical ...

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Remote Data Scientist Deep Learning information

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$36.7K

$120K

$192.1K

How much do remote data scientist deep learning jobs pay per year?

As of Aug 20, 2026, the average yearly pay for remote data scientist deep learning in Jupiter, FL is $120,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,300.00 and $133,000.00 per year, depending on experience, location, and employer.

What is a remote data scientist specializing in deep learning?

Remote data scientists specializing in deep learning are professionals who use advanced machine learning techniques, particularly deep neural networks, to analyze large amounts of data and extract meaningful insights. They work from remote locations, leveraging digital tools to build, train, and deploy deep learning models for tasks such as image recognition, natural language processing, and predictive analytics. These experts collaborate with other team members virtually, contributing to projects in industries like healthcare, finance, and technology without needing to be physically present in an office.

What are the key skills and qualifications needed to thrive as a remote data scientist specializing in deep learning?

To thrive as a Remote Data Scientist specializing in Deep Learning, you need a strong background in mathematics, statistics, programming (especially Python), and experience with deep learning frameworks such as TensorFlow or PyTorch, often supported by a relevant degree. Familiarity with cloud platforms (e.g., AWS, GCP), version control systems like Git, and certifications in machine learning are highly beneficial. Strong analytical thinking, problem-solving abilities, and effective remote communication skills help you stand out in this position. These skills and qualities are essential for designing robust models, collaborating with distributed teams, and delivering impactful AI solutions.

How do remote data scientists specializing in deep learning typically collaborate with cross-functional teams?

Remote Data Scientists in Deep Learning often work closely with software engineers, product managers, and domain experts through virtual meetings, shared documentation, and version-controlled code repositories. They collaborate on defining project goals, sharing model insights, and integrating machine learning solutions into products. Effective communication and clear documentation are crucial, as team members may be in different time zones or have varying technical backgrounds. Tools like Slack, JIRA, and GitHub are commonly used to streamline collaboration and track progress.

What are popular job titles related to Remote Data Scientist Deep Learning jobs in Jupiter, FL?

For Remote Data Scientist Deep Learning jobs in Jupiter, FL, the most frequently searched job titles are:

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Remote Data Scientist Deep Learning jobs near you

Computational Physics Specialist - Remote

micro1 AI

Port Saint Lucie, FL • Remote

$80 - $140/hr

Part-time

Posted 17 days ago

Job description

Role Title: Physics Expert (PhD / Postdoc)


Role Type: Contractor.


Location: Remote


micro1 is engaging Physics Experts (PhD / Postdoc) to contribute deep scientific knowledge and problem-solving skills to a high-impact customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Solve advanced physics problems from your specialization, delivering rigorous, well-documented derivations and analyses.
  2. Produce technically precise, clearly written solutions, detailing all assumptions, approximations, and final results using LaTeX mathematical notation.
  3. Utilize SymPy, Python, and Jupyter for symbolic or numerical verification and clear computational workflows where relevant.
  4. Identify and articulate subtleties in problem statements, including special cases, boundary conditions, and dimensional consistency.
  5. Flag ambiguities in project materials, proposing well-reasoned interpretations and clarifications as needed.
  6. Iterate on submitted solutions in response to feedback from project reviewers, ensuring corrections are cleanly integrated.
  7. Uphold rigorous standards in documentation and reproducibility consistent with professional research practice.


Preferred Qualifications

  1. PhD in physics or advanced-stage PhD candidacy, with active research experience in a relevant subfield.
  2. Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter (including moiré systems, magnetism, PXP/Rydberg), AMO/Quantum Optics, Gravitation, Cosmology, Astrophysics, Quantum Information, or Optical Properties of Materials.
  3. 2–5 recent representative publications (past ~5 years) in your field, with accessible arXiv or DOI records.
  4. Proficiency with LaTeX for presenting mathematics, and with SymPy, Python, and Jupyter for computational work; willingness to indicate areas for further support if needed.
  5. Demonstrated excellence in written technical communication, with a track record of producing clear, precise, and well-argued scientific outputs.
  6. Strong analytical skills, able to isolate key physical principles and provide nuanced solutions to complex problems.
  7. Availability to engage with the project consistently over an 8–10 week period (approx. 10 hours/week).

Apply