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Entry Level Ai Data Engineer Jobs in Nevada (NOW HIRING)

micro1 AI

Bioinformatics Software Engineer

Henderson, NV · Remote

$80 - $110/hr

... AI-driven discovery platforms. * Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources. * Provide ...

Allegiant

Software Engineer in Test (SET)

Las Vegas, NV · On-site

$80.40 - $97.90/hr

In addition to traditional test automation, the SET applies AI assisted tooling and creative ... Basic knowledge of SQL and validating data across system layers. * Strong problem solving ...

TERRACON

Field Engineer

Las Vegas, NV · On-site

... data wherever projects are located. From AI-supported solutions and predictive technologies to ... engineering and scientific expertise to solving our clients' challenges and achieve their goals for ...

TERRACON

Field Engineer

Las Vegas, NV

... data wherever projects are located.From AI-supported solutions and predictive technologies to ... Engineering Intern (Engineer in Training) (Or ability to obtain) * Follow safety rules, guidelines ...

Latent AI

Operations Engineer

Las Vegas, NV · On-site

$70 - $95/hr

Las Vegas, NV | ENGINEERING, Field Engineering | In office | Full-time The Boring Company is ... Monitor subsystem operational data, analyze performance trends, and implement improvements to ...

RadNet, Inc.

Computer Scientist II

Las Vegas, NV · On-site

$101.92 - $110.24/hr

Design and implement Retrieval-Augmented Generation (RAG) architectures and AI-driven workflows ... Advanced proficiency in Python programming for software development, automation, data engineering ...

JT4, LLC

Computer Scientist II

Las Vegas, NV · On-site

Design and implement Retrieval-Augmented Generation (RAG) architectures and AI-driven workflows ... Advanced proficiency in Python programming for software development, automation, data engineering ...

JT4 LLC

Computer Scientist II

Las Vegas, NV · On-site

Design and implement Retrieval-Augmented Generation (RAG) architectures and AI-driven workflows ... Advanced proficiency in Python programming for software development, automation, data engineering ...

JLL

Data Collection Specialist II

Las Vegas, NV · Remote

Bachelor's degree (BA/BS) in engineering, construction management, sciences, IT, or related field a ... Using AI capabilities, we analyze your application for relevant skills, experiences, and ...

TEKsystems

Data Center Technician

Reno, NV

$30 - $32/hr

Collaborate with engineering, operations, and infrastructure teams to maintain data center ... Support infrastructure powering the future of AI, cloud computing, and advanced technology ...

TEKsystems

Data Center Technician

Reno, NV

$30 - $32/hr

Collaborate with engineering, operations, and infrastructure teams to maintain data center ... Support infrastructure powering the future of AI, cloud computing, and advanced technology ...

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Entry Level Ai Data Engineer information

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, understand data pipelines and databases, and gain experience with cloud platforms such as AWS or Azure. Completing relevant certifications or courses in data engineering and machine learning can also improve job prospects.

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 Entry Level Ai Data Engineer jobs in Nevada?

For Entry Level Ai Data Engineer jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Engineer jobs in Nevada look for?

The top searched job categories for Entry Level Ai Data Engineer jobs in Nevada are:

What cities in Nevada are hiring for Entry Level Ai Data Engineer jobs?

Cities in Nevada with the most Entry Level Ai Data Engineer job openings:

Entry Level Ai Data Engineer jobs near you
Infographic showing various Entry Level Ai Data Engineer job openings in Nevada as of July 2026, with employment types broken down into 63% Full Time, 12% Part Time, and 25% Contract. Highlights an 88% In-person, and 12% Remote job distribution.

Bioinformatics Software Engineer

micro1 AI

Henderson, NV • Remote

$80 - $110/hr

Part-time

Posted 19 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.

Apply