Job description

Job Purpose GCubed, Inc. is seeking an AI/ML Engineer to design, build, and deploy machine learning models and AI-powered solutions that solve real business problems. This role will work closely with engineering, product, data, and business teams to turn complex data into scalable, practical, and measurable solutions. The ideal candidate has strong technical skills, curiosity, problem-solving ability, and experience with Large Language Models (LLMs). Essential Functions of the Job • Design, develop, train, and deploy machine learning and AI models. • Build scalable ML pipelines for data processing, model training, testing, and deployment. • Work with structured and unstructured data, including text, images, documents, and large datasets. • Collaborate with data engineers, software engineers, and product teams to integrate AI/ML solutions into applications. • Evaluate model performance and improve accuracy, efficiency, reliability, and scalability. • Research and apply current AI/ML methods, tools, and best practices. • Support development of predictive models, recommendation systems, NLP tools, automation workflows, and generative AI solutions. • Monitor deployed models and troubleshoot issues related to drift, bias, performance, and data quality. • Document model architecture, assumptions, limitations, and performance metrics. • Ensure responsible AI practices, including privacy, security, fairness, and compliance. Required Qualifications • Minimum active secret clearance • Bachelor’s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, Engineering, or related field. • 3+ years of experience in machine learning, AI, data science, or software engineering. • Strong programming experience with Python. • Experience with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost. • Experience building and deploying machine learning models in production. • Strong understanding of algorithms, model evaluation, feature engineering, and statistical analysis. • Experience working with large datasets and data processing tools. • Familiarity with APIs, cloud platforms, and modern software development practices. • Ability to communicate technical concepts clearly to non-technical stakeholders. Preferred Qualifications • Master’s degree or PhD in a related field. • Experience with Generative AI, LLMs, NLP, computer vision, or deep learning. • Experience with tools such as LangChain, Hugging Face, OpenAI API, Azure AI, AWS SageMaker, or Google Vertex AI. • Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, or CI/CD pipelines. • Experience with SQL, Spark, Databricks, Snowflake, or cloud data warehouses. • Knowledge of model governance, AI ethics, bias testing, and data privacy standards. • Experience deploying AI solutions in enterprise environments. • Experience with Ask Sage Technical Skills • Languages: Python, SQL, R preferred • ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost • Cloud Platforms: AWS, Azure, or Google Cloud • MLOps: Docker, Kubernetes, MLflow, Airflow, CI/CD • Data Tools: Pandas, NumPy, Spark, Snowflake, Databricks • AI/LLM Tools: Hugging Face, LangChain, OpenAI, vector databases Working Conditions Primarily in an office environment. Physical Requirements The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms. The employee is occasionally required to sit; climb or balance; and stoop, kneel, crouch or crawl. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. Benefits GCubed offers the following benefits to full time employees: Medical Insurance, Dental Insurance, Vision Insurance, Company Paid Life Insurance, Short Term Disability, Flexible Spending Account, 401k Retirement Savings Plan with Company Match, Tuition and Professional Development Assistance, 529 College Savings Plan and Tricare Supplement Insurance. EEO Statement GCubed, Inc. does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

Requirements

Must-haves

Essential Functions of the Job
Design, develop, train, and deploy machine learning and AI models.
Build scalable ML pipelines for data processing, model training, testing, and deployment.
Work with structured and unstructured data, including text, images, documents, and large datasets.
Collaborate with data engineers, software engineers, and product teams to integrate AI/ML solutions into applications.
Evaluate model performance and improve accuracy, efficiency, reliability, and scalability.
Research and apply current AI/ML methods, tools, and best practices.
Support development of predictive models, recommendation systems, NLP tools, automation workflows, and generative AI solutions.
Monitor deployed models and troubleshoot issues related to drift, bias, performance, and data quality.
Document model architecture, assumptions, limitations, and performance metrics.
Ensure responsible AI practices, including privacy, security, fairness, and compliance.
Minimum active secret clearance

Nice-to-haves

Master’s degree or PhD in a related field.
Experience with Generative AI, LLMs, NLP, computer vision, or deep learning.
Experience with tools such as LangChain, Hugging Face, OpenAI API, Azure AI, AWS SageMaker, or Google Vertex AI.
Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, or CI/CD pipelines.
Experience with SQL, Spark, Databricks, Snowflake, or cloud data warehouses.
Knowledge of model governance, AI ethics, bias testing, and data privacy standards.
Experience deploying AI solutions in enterprise environments.
Experience with Ask Sage
Technical Skills
Languages: Python, SQL, R preferred
ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost
Cloud Platforms: AWS, Azure, or Google Cloud

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningpythonapiazureawsdockerkubernetesci/cdsqlllm

Platform: paycom
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Professional Development