AI / Machine Learning Engineer

MCI Careers•,

5d•Onsite

About The Position

MCI is seeking a highly analytical and technically skilled AI / Machine Learning Engineer to develop, deploy, and optimize machine learning solutions that drive business innovation and operational efficiency. This role is responsible for building scalable AI systems, developing predictive models, and transforming complex datasets into actionable insights that support strategic decision-making. You will collaborate with data scientists, software engineers, product teams, and business stakeholders to deliver robust AI solutions that solve real-world challenges and create measurable business value. To be considered for this role, you must complete a full application on our company careers page, including all screening questions and a brief pre-employment test.

Requirements

Bachelor's Degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, Artificial Intelligence, or a related field.
Minimum 3 years of experience developing machine learning or AI solutions.
Strong proficiency in Python and machine learning development practices.
Experience building, training, evaluating, and deploying machine learning models.
Knowledge of supervised, unsupervised, and deep learning methodologies.
Experience working with large datasets and data preprocessing techniques.
Understanding of statistical modeling, predictive analytics, and model optimization.
Experience integrating machine learning solutions into production environments.
Familiarity with software engineering principles and version control systems.
Knowledge of cloud computing platforms and distributed computing environments.
Strong analytical thinking and problem-solving capabilities.
Ability to communicate complex technical concepts to technical and non-technical stakeholders.

Nice To Haves

Experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, or similar frameworks.
Experience with MLOps, CI/CD pipelines, and model lifecycle management.
Exposure to Generative AI and Large Language Models.
Experience with data engineering or ETL pipelines.
Knowledge of containerization technologies such as Docker and Kubernetes.
Familiarity with data visualization and reporting tools.
Experience in NLP, computer vision, or recommendation systems.
Industry certifications related to AI, machine learning, or cloud technologies.

Responsibilities

Design, develop, and deploy machine learning models that support business objectives and enhance operational performance.
Build and train supervised, unsupervised, and deep learning models.
Develop predictive analytics and intelligent automation solutions.
Perform feature engineering and data preparation activities.
Evaluate model performance and implement continuous improvements.
Ensure machine learning solutions are scalable, reliable, and production-ready.
Deploy models into production environments.
Develop and maintain model serving infrastructure.
Monitor model performance and address drift or degradation.
Support model retraining and lifecycle management processes.
Develop efficient data pipelines and workflows that support AI initiatives.
Collaborate with data teams to prepare and process large datasets.
Optimize data collection, transformation, and storage processes.
Ensure data quality and integrity across machine learning workflows.
Support integration with enterprise systems and platforms.
Maintain high standards of quality, security, and compliance across AI solutions.
Implement testing and validation procedures.
Ensure models align with governance and regulatory requirements.
Document methodologies, processes, and technical solutions.
Support responsible AI and ethical AI practices.
Stay current with advancements in AI and machine learning technologies.
Evaluate emerging machine learning frameworks and tools.
Research innovative approaches to solving business challenges.
Recommend enhancements to AI architectures and development practices.
Contribute to continuous improvement initiatives across the AI function.