Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and optimizing high-scale MLOps infrastructure and distributed systems with an accent on production-grade model deployment, data pipeline reliability, and observability. Focus on transitioning research prototypes into resilient microservices while balancing latency, throughput, and cost-efficiency in a complex AI security ecosystem.

Location: Must be based in South Africa

Company

hirify.global is a global leader in Human Risk Management, providing a platform that combines continuous risk intelligence and personalized training to protect organizations against AI-powered cyberthreats.

What you will do

• Design, develop, and research robust Machine Learning systems for production environments.
• Build and harden high-throughput, distributed microservices to support AI-driven intelligence products.
• Drive the deployment and optimization of predictive models and LLM architectures.
• Implement automated pipelines for data and model versioning, validation, and retraining.
• Develop advanced observability tools to monitor model drift, data integrity, and system health.
• Apply clean code practices and participate in rigorous cross-team code reviews.

Requirements

• Must be based in South Africa.
• English language proficiency (resume submission required in English).
• BS degree with 3+ years of relevant experience or MS/Ph.D. with equivalent background.
• Strong production-grade development skills in Python and PyTorch.
• Hands-on experience with AWS (SageMaker, Lambda) and containerization/IaC tools (Docker, Terraform).
• Proficiency in distributed data processing using Apache Spark.

Nice to have

• Experience with Feature Stores or automated feature engineering.
• Familiarity with C# and JavaScript.
• Experience with secure coding practices.

Culture & Benefits

• Company-wide performance-based bonuses.
• Comprehensive support including tuition and certification reimbursement programs.
• Adoption assistance and referral bonuses.
• Modern, high-tech, and collaborative work environment.

Hiring process

• Application screening.
• Potential applicant assessment and background check.