Job Description

POSITION SUMMARY

We are seeking a skilled AI/ML Ops Engineer to join our growing Data & Automation team. This role will be instrumental in operationalizing machine learning models and AI solutions across the enterprise, ensuring they are scalable, reliable, and aligned with ETS’s strategic goals.

PRIMARY RESPONSIBILITIES

• Design, build, and maintain scalable AIML pipelines and infrastructure for model training, deployment, and monitoring.
• Collaborate with data scientists, engineers, and business stakeholders to productionize AI/ML models.
• Implement CI/CD pipelines for ML workflows using tools like MLflow, Kubeflow, SageMaker, Bedrock, or Azure ML service.
• Monitor model performance, drift, and retraining needs using observability tools and dashboards.
• Develop and implement comprehensive AI/ML model testing strategies during development, deployment, and recalibration phases.
• Lead training and retraining of ML models while providing metrics to document and track performance.
• Ensure compliance with AI/data governance, security, and ethical AI standards.
• Automate data ingestion, feature engineering, and model deployment processes.
• Develop and implement comprehensive AI/ML
• Work effectively within agile development frameworks and collaborate across cross-functional teams.
• Communicate technical findings, model performance insights, and recommendations clearly to senior leadership.

KNOWLEDGE/SKILLS

• Experience with AI/ML lifecycle tools (e.g., MLflow, Airflow, SageMaker, Bedrock, Vertex AI, Azure Open AI).
• Experience with ML frameworks (like Keras or PyTorch) and libraries (scikit-learn)
• Strong understanding of model versioning, reproducibility, and monitoring.
• Familiarity with data pipelines, APIs, and microservices architecture.
• Excellent problem-solving and communication skills.
• Experience with LLM platforms and frameworks such as Lang Chain, Crew, Azure Open AI
• Experience with LLMOps or deploying generative AI models.
• Knowledge of AI/data privacy, model explain ability, and responsible AI practices.
• Exposure to BI tools and data visualization platforms (e.g., Power BI, Tableau).

Required:

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
• 5+ years of experience in AI/ML Ops, DevOps, or Data Engineering roles.

Mandatory Competencies