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Remote Machine Learning Jobs in Fayetteville, GA

Smarsh

Lead Data Scientist

Atlanta, GA · Remote

$166K - $214K/yr

Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities * Data annotation and quality review

Revenue Analytics

Data Scientist

Atlanta, GA · Remote

$95K - $110K/yr

As a Data Scientist, you will help build machine learning and AI systems that power our hospitality analytics platform. You will work on revenue management and pricing problems in a complex, fast ...

Revenue Analytics

Data Scientist

Atlanta, GA · On-site +1

$95K - $110K/yr

As a Data Scientist, you will help build machine learning and AI systems that power our hospitality analytics platform. You will work on revenue management and pricing problems in a complex, fast ...

micro1 AI

AI Trainer - Microbiology Expert

Atlanta, GA · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

... and machine learning models. What We Are Looking For: We are seeking an experienced and highly ... Flexible work environment and remote work options. Join us and be part of a team building ...

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · Remote

$117K - $140K/yr

... and machine learning models. What We Are Looking For: We are seeking an experienced and highly ... Flexible work environment and remote work options. Join us and be part of a team building ...

The Data Sherpas

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

... and machine learning models. What We Are Looking For: We are seeking an experienced and highly ... Flexible work environment and remote work options. Join us and be part of a team building ...

Worldpay

Principal Data Scientist

Atlanta, GA · On-site +1

$165K - $249K/yr

Candidates must be a US Citizen or Green Card Holder This position is remote in the Greater Boston ... Expertisein machine learning, statistical modeling, and dataanalysis,strong experience across the ...

Unum UK

Data Scientist II - CX Analytics

Atlanta, GA · On-site +1

Current remote and field-based Unum employees may apply and will be considered in accordance with ... Conducts end-to-end machine learning tasks from problem synthesis to model deployment. * Data ...

Motorola

Senior DevOps Engineer (US REMOTE)

Atlanta, GA · Remote

$140K - $170K/yr

Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ... Candidate can live anywhere in the United States. #LI-MP2 #LI-REMOTE Basic Requirements * 8+ years ...

FirstBank

Senior Automation Developer

Atlanta, GA · Remote

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

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Showing results 21-40

All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Fayetteville, GA

Remote Machine Learning information

See Fayetteville, GA salary details

$22.4K

$37.4K

$77.3K

How much do remote machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for remote machine learning in Fayetteville, GA is $37,406.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,500.00 and $40,400.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What cities near Fayetteville, GA are hiring for Remote Machine Learning jobs? Cities near Fayetteville, GA with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Fayetteville, GA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $37,406 per year, or $18 per hour.

Lead Data Scientist

Smarsh

Atlanta, GA • Remote

$166K - $214K/yr

Full-time

Re-posted 20 days ago

Job description

Who are we?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines.  Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

Summary
 
As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You’ll work on highly specialized problems at the intersection of natural language processing, communications intelligence, financial supervision, and regulatory compliance, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk.
 
The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both technical excellence in NLP modeling and a deep understanding of financial domain behavior—including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.
 
This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.
How will you contribute?
  • Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.
  • Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication).
  • Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities
  • Data annotation and quality review 
  • Exploratory data analysis and model fail state analysis 
  • Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.
  • Client/prospect guidance in machine learning model and analytic fine-tuning/development processes
  • Provide guidance to junior team members on model development and EDA
  • Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team’s tooling, technique and procedures
  • Continued self-led personal development
What will you bring?
  • Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology
  • Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse
  • Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc…)
  • Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)
  • Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc…)
  • Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)
  • Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo
  • Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes
  • Familiarity with Deep Learning techniques for NLP.
  • Familiarity with LLMs - using ollama & Langchain
  • Excellent verbal and written skills
  • Proven collaborator, thriving on teamwork
 
Preferred Qualifications
  • Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field
  • Familiarity with cloud computing platforms (AWS, GCS, Azure)
  • Experience with automated supervision/surveillance/compliance tools
 
The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
 
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
 
Local cost of living assessments are done for each new hire at the time of offer.
About our culture

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.