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Remote Ai Data Engineer Jobs in Nevada (NOW HIRING)

... IL, Remote-MI, Remote-NJ, St. Louis, Missouri Details Kemper is one of the nation's leading ... This includes enterprise cloud infrastructure, developer platforms, data platforms, AI platforms ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

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Remote Ai Data Engineer information

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 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 the most commonly searched types of Ai Data Engineer jobs in Nevada? The most popular types of Ai Data Engineer jobs in Nevada are:
What are popular job titles related to Remote Ai Data Engineer jobs in Nevada? For Remote Ai Data Engineer jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Remote Ai Data Engineer jobs in Nevada look for? The top searched job categories for Remote Ai Data Engineer jobs in Nevada are:
What cities in Nevada are hiring for Remote Ai Data Engineer jobs? Cities in Nevada with the most Remote Ai Data Engineer job openings:

Digital Chemistry Specialist - Remote

micro1 AI

Sparks, NV • Remote

$90 - $120/hr

Part-time

Posted 9 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative 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 complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.