Machine Learning Integration Engineer

2 weeks ago

Singapore Unison Consulting Pte Ltd Full time

This **ML / Integration Engineer** role focuses on building and integrating **Generative AI** and **Agentic AI** solutions into enterprise environments. You will work closely with data scientists, architects, and DevOps teams to design, implement, and optimize AI pipelines and infrastructure.

**Key Responsibilities**:

- Integrate AI models into production environments using containerized platforms such as **OpenShift** and **Kubernetes**.
- Collaborate with **cross-functional teams** to understand AI workflows and translate them into robust engineering solutions.
- Develop and maintain **automation scripts** using **Linux shell scripting**, **Python**, or other relevant tools.
- Ensure seamless **deployment** and **integration of AI services** in **cloud environments** (e.g., AWS, Azure, GCP).
- Implement and maintain **network security protocols** to safeguard AI systems and data pipelines.
- Monitor and optimize system **performance**, **reliability**, and **scalability**.
- Support **CI/CD processes** and **infrastructure** for AI model deployment and updates.

**Requirements**:

- Bachelor’s degree in Computer Science, Engineering, or a related field.
- **4+ years** of experience in Machine Learning engineering or AI system integration.
- Hands-on experience with **OpenShift, Docker,** **Kubernetes**.
- Knowledge of **cloud** platforms (e.g. **AWS**, GCP) is a must-have.
- Exposure to **data and network** **security** and **compliance** in AI systems.
- Understanding of **Generative AI**and **Agentic AI concepts**.
- Experience with **LLM** prompt engineering, or RAG pipelines.
- Knowledge of API **integration** and **microservices** architecture.
- Proficiency in **Python** used both for ML and automation tasks
- Good knowledge of **Bash** and **Unix/Linux** command-line toolkit is a must-have.
- Knowledge of **Workflow Orchestrator**, such as **Ctrl-M**:

- Knowledge of **Logging and Monitoring** tools, such as **Splunk** and **Geneos**.
- Experience with **Observability framework**, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

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