Artificial Intelligence Developer

Hendrickson•Woodridge, IL

About The Position

The Artificial Intelligence (AI) Developer designs, develops, and implements scalable AI and machine learning (ML) solutions that improve business operations, decision-making, and digital capabilities. Working closely with Information Technology (IT), data, and business stakeholders, this role translates business needs into production-ready solutions while ensuring alignment with enterprise architecture, data governance, cybersecurity standards, and continuous innovation.

Requirements

A bachelor’s degree in a computer science, IT, or related field is required.
Education, training, or hands-on experience in ML, deep learning, neural networks, and predictive modeling is required.
Strong training or experience in programming languages is essential.
Training or education with cloud platforms, preferably Microsoft Azure, is necessary.
A minimum of 7 years’ experience in a software-related field.
A minimum of 2 year’s experience in an AI development related role.
Demonstrated experience with artificial intelligence and machine learning concepts, including development training, evaluation, and deployment.
Experience with statistics, predictive analytics, data science, and reporting, including applying analytical techniques to real‑world business problems.
Proficiency in programming and scripting, including experience with languages commonly used in AI and software development such as, but not limited to, Python.
Experience with data collection, cleaning, preprocessing, manipulation, and pipeline management for structured and unstructured datasets.
Familiarity with web development concepts, Application Programming Interfaces (APIs), or system integrations supporting AI or data‑driven applications.
Foundational experience with cloud platforms, especially Microsoft Azure, and familiarity with deploying or supporting applications or services.
Strong analytical, mathematical, and problem‑solving skills, with the ability to troubleshoot complex technical issues.
Understanding of the software development lifecycle (SDLC), version control, testing, and documentation practices.
Ability to work independently, manage multiple priorities, and meet deadlines in a fast‑paced environment.
Strong verbal, written, and interpersonal communication skills, with the ability to work effectively with cross‑functional teams and stakeholders at all organizational levels.
Ability to communicate project status clearly, identify risks or issues, and escalate concerns appropriately.

Nice To Haves

A master’s degree in computer science, IT, or a related field is a plus.
Related professional certifications such as, but not limited to Azure AI Engineer, Azure Data Scientist, or other AI/ML certifications are a plus.
Prior experience in a manufacturing environment, particularly within the commercial automotive industry, is desirable but not required.

Responsibilities

Design, build, fine‑tune, test, deploy, and maintain scalable AI, ML models, and solutions using modern AI services, algorithms, neural networks, GenAI, Agentic AI, and deep learning architectures.
Conduct research, experimentation, and testing to develop predictive models and innovative AI solutions that enhance business capabilities and operational efficiency.
Develop and manage data pipelines, datasets, and model training workflows, ensuring high‑quality data for training, validation, and evaluation.
Leverage big data computation and storage tools to create prototypes and handle large volumes of structured and unstructured data efficiently.
Integrate AI solutions into existing applications, web services, and business workflows, ensuring smooth deployment, scalability, and performance, particularly within Azure cloud environments.
Collaborate closely with cross‑functional teams, including IT, data, and business stakeholders, to identify needs, access and prepare datasets, and translate requirements into production‑ready AI solutions.
Continuously monitor, evaluate, and optimize model and system performance to achieve optimal accuracy, reliability, and efficiency.
Ensure AI systems align with enterprise architecture standards, data governance policies, cybersecurity requirements, and responsible AI practices.
Provide technical support for business‑critical situations, assist with reporting and analysis, and troubleshoot issues related to AI systems and applications.
Document AI models, systems, development processes, and workflows, and prepare technical documentation or training materials as needed.
Stay current with advancements in AI, ML, and cloud technologies, applying new techniques and best practices to drive continuous improvement.
Perform other related duties as assigned.