Ai / Machine Learning Engineer

Mci Careers; Cape Town; On-site; ZAR 600,000 - 1,200,000; Full time

Job summary

MCI Careers in USA/cross-border operations seeks an experienced AI / Machine Learning Engineer to design, develop, deploy, and optimize scalable ML systems. You will collaborate with data scientists, software engineers, and business stakeholders to deliver robust AI solutions and measurable business value.

The role emphasizes production-ready models, governance, and ongoing optimization in dynamic environments, with opportunities to influence AI strategy and innovation.

Qualifications

• Bachelor's degree in CS, data science, math, engineering, AI, or related field.
• Minimum 3 years of experience developing ML or AI solutions.
• Strong proficiency in Python and ML development practices.
• Experience building, training, evaluating, and deploying ML models.
• Knowledge of supervised, unsupervised, and deep learning.
• Experience with large datasets and data preprocessing.
• Understanding of statistical modeling and model optimization.
• Experience deploying ML solutions into production environments.
• Familiarity with software engineering and version control.
• Knowledge of cloud platforms and distributed computing.

Responsibilities

• Design, develop, and deploy ML models to support business objectives and improve ops.
• Build supervised, unsupervised, and deep learning models.
• Develop predictive analytics and intelligent automation solutions.
• Perform feature engineering and data prep tasks.
• Evaluate models and implement improvements.
• Ensure models are scalable and production-ready.
• Deploy models and maintain serving infrastructure.
• Monitor performance and address drift or degradation.
• Support model retraining and lifecycle management.
• Develop data pipelines and collaborate with data teams.
• Optimize data collection, transformation, and storage.
• Ensure data quality across ML workflows.
• Support integration with enterprise systems.
• Maintain governance, quality & compliance across AI solutions.
• Document methodologies and solutions.
• Promote responsible and ethical AI practices.
• Stay current with AI advancements and evaluate new tools.

Skills

Python

ML development

Data preprocessing

Productionizing ML

Cloud computing

Analytical thinking

Communication

Education

Bachelor's Degree in Computer Science / Data Science / Mathematics

Tools

TensorFlow

PyTorch

Scikit-learn

XGBoost

Docker

Kubernetes

CI/CD

MLflow

Job description

Position Overview

MCI is one of the fastest-growing tech-enabled business services companies in the USA, with a strong call center footprint and operations that extend across multiple countries. We deliver Customer Experience (CX), Business Process Outsourcing (BPO), and Anything-as-a-Service (XaaS) cloud technology solutions across a wide range of industries, including healthcare, retail, government, education, telecom, technology e-commerce, and financial services. Our contact centers are powered by both on-site and remote agents, leveraging advanced technologies to enhance customer journeys, drive scalability and reduce costs.

We are 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.

Position Responsibilities

Machine Learning Development

• 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.

Model Deployment & Production Support

• 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.

Data Engineering & Optimization

• 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.

Governance, Quality & Compliance

• 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.

Research & Innovation

• 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.

Candidate Qualifications

• 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 Have

• 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.

Physical Requirements

This job operates in a professional office environment. While performing the duties of this job, the employee will be largely sedentary and will be required to sit/stand for long periods while using a computer and telephone headset. The employee will be regularly required to operate a computer and other office equipment, including a phone, copier, and printer. The employee may occasionally be required to move about the office to accomplish tasks; reach in any direction; raise or lower objects, move objects from place to place, hold onto objects, and move or exert force up to forty (40) pounds.

Conditions of Employment

All MCI Locations: Must be authorized to work in the country where the job is based. Subject to the program and location of the position. Must be willing to submit up to a LEVEL II background and/or security investigation with a fingerprint. Job offers are contingent on background/security investigation results. Must be willing to submit to drug screening. Job offers are contingent on drug screening results. (Does not apply in Canada)

Reasonable Accommodation

Consistent with the Americans with Disabilities Act (ADA), it is the policy of MCI and its affiliates to provide reasonable accommodations when requested by a qualified applicant or employee with a disability unless such accommodations would cause undue hardship. The policy regarding requests for reasonable accommodation applies to all aspects of employment. If reasonable accommodations are needed, please contact Human Resources.

Equal Opportunity Employer

MCI does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations, and ordinances. MCI maintains a work environment free from discrimination and one where employees are treated with dignity and respect. All employees share in the responsibility for fulfilling MCI's commitment to a diverse and equal opportunity work environment. MCI will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. MCI will not tolerate discrimination or harassment based on any of these characteristics. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of MCI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where an employee works.