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Ai Ml Data Engineer Jobs in Normal, IL (NOW HIRING)

Codvo.ai

Data Scientist (Dallas)

Texas, IL

We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity ...

Mind Robotics

Forward Deployed Engineer

Normal, IL · On-site

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the ... You'll be responsible for our fleet of data collection devices - diagnosing and repairing devices ...

Steampunk

DevSecOps Engineer

Bloomington, IL · On-site

$80 - $175/hr

As a DevSecOps Engineer you will work with AI Engineers, Application Engineers, and Data Scientist to make the AI Applications we are creating Production ready. This includes application security ...

New

Munich RE

Principal Data Scientist

Bloomington, IL · On-site

Experience in multiple programming languages, including R and Python. * Deep understanding of GLMs ... Familiarity with AI and machine learning concepts, including supervised and unsupervised learning ...

Varsity Tutors

Machine Learning Tutor

Normal, IL · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

Munich Re

Principal Data Scientist - FCAS

Bloomington, IL · On-site +1

Experience in multiple programming languages, including R and Python. * Deep understanding of GLMs ... Familiarity with AI and machine learning concepts, including supervised and unsupervised learning ...

Varsity Tutors

Data Science Tutor

Normal, IL · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Trilon

Design Engineer

East Peoria, IL · On-site

Interpret survey data, GIS data, field notes, and technical reports for use in project designs ... We may use AI-powered tools to support administrative aspects of recruiting, including sourcing ...

Fehr Graham

Design Engineer

East Peoria, IL

$60K - $85K/yr

Interpret survey data, GIS data, field notes, and technical reports for use in project designs ... We may use AI-powered tools to support administrative aspects of recruiting, including sourcing ...

Rivian

People Systems Solution Analyst

Normal, IL

$107K - $133K/yr

Evaluate and pilot emerging Workday AI features (e.g., Workday Illuminate, ML-based recommendations) and assess their fit with organizational requirements, data privacy standards, and change ...

Countryfinancial

Solution Architect

Bloomington, IL · On-site

$161K - $222K/yr

Develops strategies for enterprise data ecosystems, cloud platforms, analytics, AI enablement, and ... using DevOps tools and concepts.- Collaborates with other areas to develop standards and best ...

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All JobsAi Ml Data Engineer JobsAi Ml Data Engineer Jobs in Normal, IL

Ai Ml Data Engineer information

See Normal, IL salary details

$43.5K

$126.8K

$173.5K

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

As of Aug 19, 2026, the average yearly pay for ai ml data engineer in Normal, IL is $126,819.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,900.00 and $134,400.00 per year, depending on experience, location, and employer.

What is an AI ML data engineer?

AI/ML Data Engineers are professionals who design, build, and maintain data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) applications. They are responsible for collecting, cleaning, and organizing large datasets, ensuring data quality, and enabling data scientists and ML engineers to develop and deploy models efficiently. Their work often involves using programming languages like Python or Scala, big data technologies, and cloud platforms. In essence, AI/ML Data Engineers bridge the gap between raw data and actionable insights in AI and ML projects.

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

To thrive as an AI/ML Data Engineer, you need a strong background in computer science, proficiency in programming languages like Python or Scala, and experience with data modeling, ETL pipelines, and machine learning concepts. Familiarity with big data tools (such as Hadoop, Spark), cloud platforms (AWS, GCP, Azure), and relevant certifications like Google Professional Data Engineer or AWS Certified Machine Learning are highly valuable. Strong problem-solving, collaboration, and communication skills help you work effectively within cross-functional teams and translate business needs into technical solutions. These skills ensure you can efficiently build scalable data architectures and support robust AI/ML solutions that drive business innovation.

What are some common challenges faced by AI ML data engineers when working on large-scale machine learning projects?

AI/ML Data Engineers often encounter challenges such as managing and optimizing massive datasets, ensuring data quality and consistency, and maintaining efficient data pipelines. They must also handle the integration of diverse data sources and collaborate closely with data scientists and software engineers to deploy machine learning models into production. Addressing scalability and performance bottlenecks is a frequent part of the role, requiring strong problem-solving skills and familiarity with distributed computing frameworks.

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

AspectAi Ml Data EngineerData Scientist
Primary FocusBuilding data pipelines, deploying ML models, managing data infrastructureAnalyzing data, developing models, deriving insights
Skills & CertificationsProgramming (Python, SQL), cloud platforms, data engineering toolsStatistics, machine learning, data analysis, Python/R
Work EnvironmentData engineering teams, cloud environments, big data platformsResearch teams, analytics departments, business units

While both roles involve working with data and machine learning, Ai Ml Data Engineers focus on building and maintaining data pipelines and deploying models, whereas Data Scientists primarily analyze data and develop predictive models. The roles often collaborate but serve different functions within data projects.

What are popular job titles related to Ai Ml Data Engineer jobs in Normal, IL?

For Ai Ml Data Engineer jobs in Normal, IL, the most frequently searched job titles are:

What job categories do people searching Ai Ml Data Engineer jobs in Normal, IL look for?

The top searched job categories for Ai Ml Data Engineer jobs in Normal, IL are:

What cities near Normal, IL are hiring for Ai Ml Data Engineer jobs?

Cities near Normal, IL with the most Ai Ml Data Engineer job openings:

Ai Ml Data Engineer jobs near you
Infographic showing various Ai Ml Data Engineer job openings in Normal, IL as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $126,819 per year, or $61 per hour.

Data Scientist (Dallas)

Codvo.ai

Texas, IL

Full-time

Re-posted 17 days ago

Job description

Data Scientist 

 

About Us: 

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.


Role Summary 

The on-site technical presence during the pilot and Wave 1. Works directly with the customer's

maintenance team to validate alerts, tune models, and build trust in the platform's outputs.

This role requires someone who can explain machine learning predictions in maintenance

engineering language, not data science jargon.


Responsibilities 

Discovery & Baseline (Weeks 1-2)

  • Conduct the BMS protocol audit alongside the customer's controls engineer - identify available tags, data quality, polling rates, historian configuration
  • Extract and analyze the 30-day historian pull - identify operating modes, load patterns, seasonal variations, and data gaps
  • Build the baseline operating profile for each monitored equipment unit
  • Review the customer's maintenance logs - identify the 3-5 known fault events that will serve as ground truth validation
  • Map the customer's equipment taxonomy to NEIO's equipment family catalog - confirm coverage, flag gaps

Model Tuning & Validation (Weeks 3-5)

  • Monitor live anomaly scores and triage the first alerts - determine true positive vs. false positive vs. ambiguous
  • Facilitate the alert review sessions with the site maintenance lead - present alerts in context, gather feedback, document site-specific operating knowledge that affects interpretation
  • Tune the physics constraint gate to the site's operating ranges - adjust thermodynamic bounds, load-dependent thresholds, equipment-specific parameters
  • Calibrate fault classification confidence thresholds - Platt scaling, ECE measurement, reliability diagram review
  • Validate time-to-failure estimates against known maintenance history
  • Document all tuning decisions and rationale - this becomes the playbook for fleet rollout

Phase 2 (Wave 1 Sites)

  • Travel to Wave 1 sites for the 1-week discovery phase at each site
  • Conduct on-site tag mapping review with each site's controls engineer
  • Facilitate the alert review session at each Wave 1 site
  • Train the offshore Data Scientist on site-specific tuning decisions so they can handle
  • Wave 2 remotely

 

 

Expected Background 

  • 5+ years in applied data science or machine learning - predictive maintenance, anomaly detection, or industrial process optimization
  • Strong understanding of time-series analysis, classification models (XGBoost, LightGBM), and calibration techniques
  • Ability to explain model behavior to non-technical maintenance engineers - "the model flagged this because superheat is trending 3 degrees above normal for this load condition" not "the feature importance vector shows..."
  • Comfortable working on-site at a data center or industrial facility
  • Experience with HVAC, mechanical, or electrical systems is a strong advantage - someone who knows what a chiller does, what COP means, why approach temperature matters
Employment Type: FULL_TIME

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