Engineer

Job Description

The AI Systems & Machine Learning Solutions Engineer is responsible for the end-to-end lifecycle of artificial intelligence solutions, from designing custom machine learning models to architecting the automation systems that integrate these models into production environments. This individual will analyze complex business requirements to propose and build automated workflows, ensuring that AI-driven insights are seamlessly delivered through scalable technical platforms. The role requires a unique blend of statistical modeling and systems engineering to optimize operational efficiency and drive innovation.

Major Tasks, Responsibilities & Key Accountabilities

• 25% - Model Development & Training: Designs and builds custom, re-usable machine learning models (NLP, LLMs, Predictive Analytics) based on statistical modeling and data analysis to solve specific business challenges.

• 25% - Systems Automation & Integration: Architect and develop automated pipelines and ETL jobs to manage the flow of data between AI models and enterprise applications, ensuring intuitive and efficient integration.

• 25% - MLOps & Infrastructure Maintenance: Maintain comprehensive documentation for AI workflows and manage the deployment infrastructure (CI/CD, containerization) to ensure the stability and scalability of automated AI systems.

• 25% - Technical Leadership & Strategy: Act as the technical lead for AI initiatives, working with senior leadership and stakeholders to translate business obstacles into technical requirements and actionable AI roadmaps.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Education Required

The knowledge, skills, and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Years of Relevant Work Experience

4+ years in a role focused on Machine Learning development or Systems Automation.

Preferred Qualifications

• Proven experience as an AI/ML Engineer and/or Systems Automation Engineer.

• Expertise in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) and automation tools (e.g., LangChain, Airflow).

• Background in MLOps, including containerization (Docker/Kubernetes) and cloud-native AI services (AWS SageMaker, Azure AI, or GCP Vertex AI).

• Knowledge of SQL queries, API design (REST/GraphQL), and database management systems.

• Analytical mind with a problem-solving aptitude and the ability to take initiative in an innovative environment.

Knowledge, Skills, Abilities and Competencies

• Action Oriented

• Collaborates

• Drives Results

• Communicates Effectively

• Customer Focus

• Strategic Mindset