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

Mid- Level Data Engineer

Denver, CO · On-site

$117K - $141K/yr

As part of the Data Engineering & Business Intelligence team, you will be responsible for ... Prepare and structure data to support advanced analytics and AI-enabled use cases by ensuring data ...

Sr. Data Engineer

Greenwood Village, CO · On-site

$115K - $139K/yr

Understanding of AI technologies and their application (kiro, claude, genAI tools) As part of the Network Analytics team, the Sr Data Engineer role is crucial in building and maintaining the data ...

Data Engineer

Denver, CO · On-site

$117K - $141K/yr

Role: Data Engineer Location: Denver, CO - 4 days per week work from Client office Please find ... We are seeking a skilled professional with strong expertise in Python, Spark, and leading AI/ML ...

New

Snowflake Data Engineer

Broomfield, CO · On-site

$74K - $110K/yr

We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of ... data engineering solutions using Snowflake, dbt, and Python, ensuring high-performance data ...

Data Engineer I-II

Brighton, CO · On-site

$97K - $127K/yr

Maintain working knowledge of Databricks' AI/ML tooling and broader industry trends, applying that ... Data Engineer I, II, and III. Positions in this series are flexibly staffed; placement and ...

Data Engineer I-II

Brighton, CO · Hybrid

$124K - $149K/yr

Maintain working knowledge of Databricks' AI/ML tooling and broader industry trends, applying that ... Data Engineer I, II, and III. Positions in this series are flexibly staffed; placement and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

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Showing results 1-20

Entry Level Ai Data Engineer information

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 is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior data scientists or AI research directors, which can offer compensation in that range including salary, bonuses, and stock options. Entry-level AI data engineering positions usually have lower salaries, but compensation can increase significantly with experience, skills, and responsibilities in the field.

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.

What engineer makes 500,000 a year?

Highly experienced senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn salaries approaching or exceeding $500,000 annually, especially with bonuses and stock options. These roles typically require advanced skills, extensive experience, and often work in high-demand industries like technology or finance.

How can I become an AI engineer with no experience?

To become an entry-level AI data engineer with no experience, focus on building foundational skills in programming languages like Python, learn about data management and machine learning concepts, and complete online courses or certifications in AI and data engineering. Gaining hands-on experience through personal projects, internships, or contributing to open-source initiatives can also help demonstrate your abilities to employers.

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.

Which 3 jobs will survive AI?

Entry Level AI Data Engineers are likely to continue being in demand as they develop and maintain AI models, requiring skills in data management, programming, and machine learning tools. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as data scientists, AI specialists, and cybersecurity analysts, are also expected to persist despite AI automation. These roles often require specialized knowledge and adaptability that AI cannot fully replicate yet.
What are the most commonly searched types of Ai Data Engineer jobs in Colorado? The most popular types of Ai Data Engineer jobs in Colorado are:
What are popular job titles related to Entry Level Ai Data Engineer jobs in Colorado? For Entry Level Ai Data Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Entry Level Ai Data Engineer jobs in Colorado look for? The top searched job categories for Entry Level Ai Data Engineer jobs in Colorado are:
Infographic showing various Entry Level Ai Data Engineer job openings in Colorado as of July 2026, with employment types broken down into 68% Full Time, 23% Part Time, and 9% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.
AI Data Foundation Research Engineer

AI Data Foundation Research Engineer

Hewlett Packard Enterprise

Fort Collins, CO • Hybrid

$113K - $136K/yr

Full-time

Posted 7 days ago


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

34th of 155 rated electronics manufacturers


Job description

AI Data Foundation Research EngineerThis role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

Successful candidate will develop new methods for context discovery, retrieval, filtering, prioritization, multi-modal data representation, advanced reasoning, tool calling, and reasoning trace validation in conversational, deep research, and agentic AI workflows. Successful candidate will also work on development of capture, management, search, enhancement and interpretation of meta-data and lineage for AI pipelines that enable reproducibility, reuse and optimization of pipelines; discovery, selection and usage of relevant high quality data for trustworthy AI outcomes across multiple AI applications; development, evaluation and testing of Foundation AI models for different modalities: Natural Language Processing - NLP, Large Language Models - LLM, Time Series Analysis, Computer Vision, AI for Science, etc., and augmentation of AI models with structured knowledge (i.e., knowledge infused learning). We are particularly interested in individuals with a background in computer systems, machine learning, deep learning, statistics, generative AI, data management, and big data pipelines, with good understanding of the current state of the art, major trends and opportunities, and a demonstrated track record in innovative research. The ideal candidate can thrive in an applied research environment, balancing significant technical contributions published externally in open source with the hands-on engineering skill to bring such contributions to practice in partnering with our internal software development teams and external partners.

Must-have Requirements
  • PhD in Computer Science or related fields with a focus on data engineering and data science, in particular Machine Learning, Deep Learning, and/or data management for AI, plus 3 years of relevant industry experience.
  • Research experience in Generative AI, Deep Learning and Machine Learning
  • Experience with advanced AI model architectures: LLMs, Time Series Foundation Models, Diffusion Models, etc.
  • Expertise with end-to-end pipelines for AI and Machine Learning and in particular the data layer underlying the pipelines (e.g., DVC, Pachyderm, Common Metadata Framework)
  • Experience in AI model development lifecycle, ML/deep learning frameworks and MLOps platforms (e.g. Pytorch/Tensorflow, MLFlow, Kubeflow, Ray)
  • Experience with agentic AI platforms (e.g., LangGraph, CrewAI, ADK, LlamaIndex, etc.)
Preferred Skills
  • Strong programming skills in Python with high proficiency in data structures and algorithms. C/C++ skills
  • Experience with CI/CD code development
  • Outstanding analytical and problem-solving skills
  • Experience with hybrid AI-HPC workflows (e.g., AI surrogate modeling, computational steering of experiments)
  • Experience with knowledge graphs and knowledge infused learning
  • Expertise in research of data and workflow management systems
  • Experience in system software performance and scalability optimization
  • Experience with multi-threaded programming, parallel processing, OOD/OOP/distributed programming
  • Experience in containerized development and orchestration tools (e.g. Kubernetes, Ezmeral)

Additional Skills:

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates

Job:

Engineering

Job Level:

TCP_03"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 126,500 - 240,500 in Colorado
The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

The estimated job application period closure is June 1 2026; this timeline is provided for transparency and internal planning purposes.

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

No Fees Notice & Recruitment Fraud Disclaimer

It has come to HPE's attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates. These scammers often seek to obtain personal information or money from candidates.

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendorswill never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.


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