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Ai Ml Data Engineer Jobs in Raleigh, NC (NOW HIRING)

ClifyX

AI ML Data Scientist

Cary, NC · On-site

ClifyX is a company specializing in data science and analytics, and they are seeking an AI ML Data ... Programming, Python, Spark • Statistical & Data Management Packages - Python - Pandas, Numpy ...

Zifo

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Understanding of AI/ML, data science concepts & cloud architecture Qualifications: * Bachelor's or Master's degree in data engineering / computer science or related field * Experience with scientific ...

Zifo

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Understanding of AI/ML, data science concepts & cloud architecture Qualifications: * Bachelor's or Master's degree in data engineering / computer science or related field * Experience with scientific ...

Zifo

Sr. Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

Understanding of AI/ML, data science concepts & cloud architecture Qualifications: * Bachelor's or Master's degree in data engineering / computer science or related field * Experience with scientific ...

Gilead

Manager, IT Data, ML & AI Engineering

Raleigh, NC · On-site

$126K - $163K/yr

AI/ML Data Scientist, US Commercial As part of our enterprise AI strategy to speed life-changing ... Design and execute prompt engineering strategies and conduct experimentation to optimize AI model ...

Sennos

Data Engineer

Durham, NC · On-site

$110K - $132K/yr

About Sennos Sennos is rapidly emerging as the global leader in AI-driven sensing, analytics, and ... Contribute to ML data preparation and feature pipeline workflows * Collaborate closely with Data ...

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All JobsAi Ml Data Engineer JobsAi Ml Data Engineer Jobs in Raleigh, NC

Ai Ml Data Engineer information

See Raleigh, NC salary details

$43.3K

$126.1K

$172.5K

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

As of Sep 7, 2026, the average yearly pay for ai ml data engineer in Raleigh, NC is $126,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $133,700.00 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 Raleigh, NC?

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

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

The top searched job categories for Ai Ml Data Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Ai Ml Data Engineer jobs?

Cities near Raleigh, NC with the most Ai Ml Data Engineer job openings:

Ai Ml Data Engineer jobs near you

AI ML Data Scientist

ClifyX

Cary, NC • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
ClifyX is a company specializing in data science and analytics, and they are seeking an AI ML Data Scientist. The role requires expertise in predictive modeling and big data analytics, with a focus on implementing machine learning techniques to solve various business problems in the banking and financial services sector.
Responsibilities:
• Data Scientist with 5-10+ years of result-oriented, hands-on professional experience with a successful record of accomplishments in Data Science & Analytics and Project management in Banking and Financial Services.
• Expertise in Predictive Modeling and Big Data Analytics, Statistical model development, Implementations & Optimization techniques
• Proficiency in implementing Machine learning techniques -Regression, Decision Tree Learning, Neural networks, Random Forest and XGBoost-in various business problems (AML, fraud detection, mortgage default, foreclosure, credit risk management, price prediction and optimization)
• Strong leadership and capacity to work as a team player, as well as excellent communication skills
• Some knowledge on various aspects of Retail and Wholesale Consumer banking and US Mortgage Banking.
Qualifications:
Required:
• Machine Learning techniques
• Unsupervised - K-means Clustering, PCA - Dimension Reduction, Kernel Density Estimations
• Supervised - Regression, Decision Trees, Random forest, XG Boost algorithm
• Time series - Exponential models, Holt-Winters, ETS, Hybrid
• ARIMA & GARCH
• Deep Learning - Neural Network, Recurrent Neural Networks
• Database - SQL, Advance SQL, Oracle, NoSQL
• Data Science Languages - SAS, SAS Enterprise Miner, R Programming, Python, Spark
• Statistical & Data Management Packages - Python - Pandas, Numpy, sklearn, PyOdbc
• R- dplyr, car, caret, lubridate, zoo, Rminer, R-Odbc
• Visualization - Tableau, Shiny, ggplot2, dygraphs, matplotlib, seaborn
• Big Data Technologies - Spark (Pyspark & SparkR), Hadoop, Yarn
• PM Tools - MS Project, MS Visio, TFS, JIRA
• Cloud, Web frameworks & Virtualization - Azure, Flask, Docker & Kubernetes, Kafka
• 5-10+ years of result-oriented, hands-on professional experience with a successful record of accomplishments in Data Science & Analytics and Project management in Banking and Financial Services
• Expertise in Predictive Modeling and Big Data Analytics, Statistical model development, Implementations & Optimization techniques
• Proficiency in implementing Machine learning techniques - Regression, Decision Tree Learning, Neural networks, Random Forest and XGBoost-in various business problems (AML, fraud detection, mortgage default, foreclosure, credit risk management, price prediction and optimization)
• Strong leadership and capacity to work as a team player, as well as excellent communication skills
• Some knowledge on various aspects of Retail and Wholesale Consumer banking and US Mortgage Banking
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
ClifyX logo

About ClifyX

Sourced by ZipRecruiter

ClifyX is a well-established player in the IT Services sector that specializes in providing result-oriented technological solutions to a wide range of industrial verticals. Based in South Plainfield, New Jersey, ClifyX offers a comprehensive selection of IT services that include project staffing, application development, professional consulting, and other IT-based solutions. While the company's website, clifyx.com, does not divulge the exact founding date, it is clear that ClifyX has grown into a renowned name within their domain, thanks to their unwavering commitment to innovative practices. The company's mission statement revolves around harnessing the power of technology to assist their clientele in steering their respective businesses towards success.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

South Plainfield, NJ, US

Year founded

1998

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