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Remote Ai Data Engineer Jobs in Sumter, SC (NOW HIRING)

micro1 AI

Bioinformatics Software Engineer

Columbia, SC · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted ...

Unum UK

Data Scientist II - CX Analytics

Columbia, SC · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Our team leverages AI across development workflows and uses it to extract insights from both ... Current remote and field-based Unum employees may apply and will be considered in accordance with ...

micro1 AI

Cheminformatics Specialist - Remote

Columbia, SC · On-site +1

$90 - $120/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work ... Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal ...

Unum UK

Principal Data Scientist - CX Analytics

Columbia, SC · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

AI and LLMs are central to how our team works, both in how we write code and in how we extract ... Current remote and field-based Unum employees may apply and will be considered in accordance with ...

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Showing results 21-40

All JobsAi Data Engineer JobsRemote Ai Data Engineer JobsRemote Ai Data Engineer Jobs in Sumter, SC

Remote Ai Data Engineer information

See Sumter, SC salary details

$39.6K

$115.5K

$158.1K

How much do remote ai data engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for remote ai data engineer in Sumter, SC is $115,522.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,000.00 and $122,500.00 per year, depending on experience, location, and employer.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a remote AI data engineer?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What are popular job titles related to Remote Ai Data Engineer jobs in Sumter, SC?

For Remote Ai Data Engineer jobs in Sumter, SC, the most frequently searched job titles are:

What cities near Sumter, SC are hiring for Remote Ai Data Engineer jobs?

Cities near Sumter, SC with the most Remote Ai Data Engineer job openings:

Remote Ai Data Engineer jobs near you
Infographic showing various Remote Ai Data Engineer job openings in Sumter, SC as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $115,522 per year, or $55.5 per hour.

Bioinformatics Software Engineer

micro1 AI

Columbia, SC • Remote

$80 - $110/hr

Part-time

Posted 14 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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