Job Description

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10+ years overall IT experience , including 5+ years in Machine Learning Engineering, MLOps, AI Platform Engineering, or AI Operations leadership

Key Responsibilities n

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- Design and implement production-grade model deployment architectures.
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- Develop CI/CD and CT (Continuous Training) pipelines for AI and ML workloads.
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- Automate model packaging, testing, validation, deployment, and rollback processes.
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- Enable scalable serving infrastructure for ML and GenAI applications.
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- Support batch, real-time, and streaming inference architectures.
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- Build and manage enterprise AI platforms on cloud and hybrid environments.
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- Implement containerized AI workloads using Docker and Kubernetes.
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- Establish scalable GPU-enabled environments for model training and inference.
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- Monitor model accuracy, drift, bias, performance, latency, and usage.
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- Establish alerting and automated remediation mechanisms.
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- Develop AI observability dashboards and operational metrics.
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- Lead root cause analysis for AI platform and model performance issues.
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4. Data & Feature Management nn
- Establish data lineage and model traceability mechanisms.
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- Define data quality controls and validation standards.
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- Govern training, validation, and inference datasets.
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- Ensure reproducibility and auditability across AI pipelines.
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5. Generative AI Operations nn
- Operationalize GenAI and LLM-based solutions.
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- Build deployment frameworks for RAG, Agentic AI, and LLM applications.
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5anage prompt versioning, evaluation frameworks, and model governance.

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- Define monitoring controls for LLM performance, hallucination rates, and response quality.
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- Support model orchestration frameworks including LangChain, LangGraph, CrewAI, and Vertex AI Agents.
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6. Stakeholder Management nn
- Collaborate with business leaders, AI teams, operations teams, and executive stakeholders.
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- Translate business requirements into scalable AI operational solutions.
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- Present AI operational status and platform roadmap updates to leadership.
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- Manage vendor and cloud provider engagements.
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Required Technical Skills Skill Area Expected Competency n

MLOps Platforms

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DevOps & Automation

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Jenkins, GitHub Actions, GitLab CI/CD,

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Containerization

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Infrastructure as Code

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Terraform, CloudFormation, Ansible

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Programming

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Python, SQL

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BigQuery, Snowflake, Spark, Airflow

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GenAI Platforms

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📌 Machine Learning Lead (Sydney)
🏢 BULLIT MANAGEMENT SERVICES
📍 Sydney