Machine Learning Integration Engineer

**About The Role**

Bounteous is a premier end-to-end digital transformation consultancy dedicated to partnering with ambitious brands to create digital solutions for today’s complex challenges and tomorrow’s opportunities. With uncompromising standards for technical and domain expertise, we deliver innovative and strategic solutions in Strategy, Analytics, Digital Engineering, Cloud, Data & AI, Experience Design, and Marketing.

One of key Financial Services clients is looking for a **Machine Learning Integration Engineer**for a position based in Singapore.

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of striking a balance between visionary thinking and practical solutions. The ability to comprehend, inspire, and mobilize others is crucial. A business-oriented mindset coupled with effective storytelling will drive your success. We are looking for self-starters ready to take on responsibilities with enthusiasm.

This **Lead 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.

**Required Qualifications**
- 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.

**What's on Offer**

Bounteous brings together 5000+ employees spanning North America, APAC, and EMEA, and partnerships with leading technology providers. Through advanced digital engineering, technology solutions, and data-driven digital experiences, we create exceptional and efficient business impact and help our clients win.

Bounteous is focused on promoting an inclusive environment and is proud to be an equal opportunity employer. We celebrate the different viewpoints and experiences our diverse group of team members bring to Bounteous. Bounteous does not discriminate on the basis of race, religion, colour, gender identity, sexual orientation, age, physical or mental disability, national origin, or any other status protected under state, or local law.