AI Engineer (Contract) GautengHybrid ISB7000178

We are seeking an Expert AI Engineer to join a specialized DevOps team.

You will lead the engineering and architectural direction for AI and Machine Learning services ensuring they are seamlessly integrated into the groups global production processes.

AI Architectural Lead: Design and implement end-to-end AI/ML architectures focusing on scalability and the reuse of services across multiple global domains.

AWS Production Specialist: 10 years of hands-on experience in AI/ML engineering with at least 3 years specifically dedicated to deploying and operating models in AWS production environments.

Technical Mentor: Act as a senior influence running training programs and mentoring junior team members to elevate the collective technical capability of the Hub.

• Contract Dates:to
• Location: Midrand/Menlyn/Rosslyn/Home Office Rotation
• Level: Expert
• Experience: 10 years

Qualifications & Experience

• Education: Degree in Computer Science Math Statistics or Engineering; MSc or PhD is preferred.
• Core Experience: Minimum 10 years of hands-on experience in AI/ML engineering and architecture.
• Cloud Focus: At least 3 years specifically deploying and operating models in AWS production environments.
• Leadership Track Record: Proven history of running training programs and influencing technical direction across teams.

Essential Skills & Technologies

• Deep AI/ML Theory: Comprehensive understanding of classical algorithms (supervised/unsupervised) probabilistic models Bayesian methods and optimization techniques.
• AWS Production Engineering: Strong experience implementing models in live environments using AWS SageMaker EC2 Lambda and EKS.
• Programming & ML Libraries: High proficiency in Python and the core stack: NumPy SciPy scikit-learn TensorFlow/PyTorch and XGBoost/LightGBM.
• Software Engineering Excellence: Professional-grade skills in code quality unit testing CI/CD and version control (Git).
• Validation & Evaluation: Proven expertise in bias detection model calibration robustness testing and validation.
• Data & Feature Engineering: Extensive experience with ETL and data pipelines using AWS Glue Redshift RDS and S3.
• End-to-End Architecture: Ability to design entire AI solutions including model serving inference scaling and monitoring/observability.
• Technical Mentorship: Proven ability to coach junior engineers/data scientists and lead workshops or code reviews.
• Communication: Exceptional skill in translating technical concepts for business stakeholders and producing high-quality design documentation.
• Governance & Security: Awareness of data privacy (access control model governance) and implementing security controls within AWS.

Advantageous Skills

• Advanced MLOps: Hands-on experience with SageMaker Pipelines MLflow Kubeflow or TFX.
• Advanced Tooling: Knowledge of probabilistic programming (Pyro Stan) and XAI techniques (SHAP LIME).
• Modern Infrastructure: Experience with Docker Kubernetes (EKS) and real-time streaming data (Kinesis Kafka).
• Cost Optimization: Experience with spot instances autoscaling and model shards for cost-optimized inference.
• Regulatory Knowledge: Familiarity with GDPR and privacy-preserving ML (differential privacy federated learning).
• Certifications: AWS Certified Machine Learning Specialty or Solutions Architect.

Role & Responsibilities

• Architectural Leadership: Lead the design and delivery of scalable production-ready AI solutions on AWS emphasizing classical AI techniques.
• Best Practice Enforcement: Define standards for the entire ML lifecycle from development and validation to deployment and monitoring.
• Pipeline Construction: Build and maintain end-to-end data and model pipelines ensuring they are reproducible and maintainable.
• Inference & Scaling: Drive decisions on model serving strategies including rollback plans and cost optimization.
• Production Oversight: Oversee model versioning drift detection and alerting for live systems.
• Upskilling & Coaching: Mentor junior staff through pair programming technical reviews and coaching on skills roadmaps.
• Review and approve technical designs and code from the team to ensure they meet security and engineering standards.
• Partner with product managers to translate complex business problems into well-scoped ML solutions.
• Ensure all models are interpretable fair and compliant with global regulatory requirements.

NB:

• South African citizens or residents are preferred. Applicants with valid work permits will also be considered.
• By applying you give iSanqa consent to process your personal information as per the POPI Act.

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