AI MLOps Engineer - Rapid Prototyping for DevSecOps

Naval Group APAC; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Naval Group Far East is seeking an AI MLOps Engineer to accelerate AI-driven prototypes that boost developer productivity across our Software Factory. You will prototype, test MVPs, and iterate on AI use cases, including code generation, testing automation, and CI/CD integration.

The role requires deep MLOps and AI experimentation experience with a focus on rapid deployment, collaboration with DevSecOps teams, and producing scalable solutions for production environments.

Qualifications

• Preferably a Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
• 1-3 years of experience in MLOps, or AI experimentation with a strong focus on rapid prototyping and MVP development.
• Proficiency in Python, Golang, Rust or other relevant languages.
• Experience with ML frameworks (TensorFlow, PyTorch, LangChain), deployment platforms (Kubernetes) and ML pipeline tools (Kubeflow, MLflow).
• Familiarity with CI/CD tools (GitLab CI)
• Knowledge of infrastructure-as-code (IaC) tools like Terraform.
• Understanding of data pipelines and tools (e.g., Apache Kafka, Spark) for data processing and transformation.
• Experience in developing Restful APIs for AI models.
• Good understanding of machine learning concepts, including neural networks, optimization algorithms, and evaluation metrics.
• Knowledge of Retrieval Augmented Generation (RAG) techniques.
• Familiarity with prompt engineering techniques like instruction design, template-based approaches, rule-based conditioning, or fine-tuning strategies.
• Demonstrated experience in developing MVPs and iterating on product prototypes with quick turnaround times.
• Skilled in conducting PoCs and building scalable solutions based on experimental results and user feedback.
• Ability to work in an agile environment with a focus on continuous experimentation and learning.
• Problem-solving skills and an innovative mindset geared towards improving developer productivity.
• Collaboration and communication skills to work effectively across DevSecOps, product, and developer teams.
• Self-driven, adaptable, and capable of managing multiple AI-driven projects in a dynamic setting.

Responsibilities

• Develop and rapidly iterate on AI-driven prototypes that support and streamline developer workflows, including code specification, code generation, and testing automation.
• Collaborate with product and DevSecOps teams to identify high-impact AI use cases that improve software development and delivery efficiency.
• Drive PoC initiatives, transforming experimental AI ideas into feasible and scalable solutions.
• Implement automation to improve repeatability and reduce manual tasks in the development pipeline, such as auto-code generation, static code analysis, and intelligent error detection.
• Integrate automation tools that improve developer productivity, streamline testing, and optimize release cycles.
• Stay current with the latest advancements in AI and machine learning technologies.
• Build Minimum Viable Products (MVPs) for new AI solutions, focusing on quick deployment, testing, and user feedback.
• Establish efficient testing and evaluation frameworks to assess the effectiveness of AI models and rapidly iterate on improvements.
• Collaborate with developers and QA teams to integrate AI-based prototypes into the broader software lifecycle and measure productivity impact.
• Design and deploy scalable ML pipelines tailored to rapidly evolving prototypes, with robust model training, testing, deployment, and monitoring processes.
• Manage versioning, model retraining, and performance tracking to ensure the continuity of high-quality AI solutions in the production environment.
• Collaborate with cross-functional teams to iterate on solutions based on developer feedback and usage data.
• Establish version control, deployment, and monitoring standards for ML models across the production environment.
• Develop tools and processes for A/B testing, canary releases, and other ML model rollout techniques.
• Ensure ML models are efficiently integrated within the internal Software Factory.
• Work closely with DevSecOps engineers to integrate ML workflows with existing CI/CD pipelines.
• Enhance and support security measures for ML processes, ensuring compliance with DevSecOps policies and protocols.
• Write scripts and automate workflows to manage ML pipeline processes, ensuring faster, reliable, and secure model deployments.
• Integrate automation into DevSecOps workflows, ensuring repeatability and reducing manual intervention.
• Document AI use cases, PoCs, MVPs, and best practices for the integration of AI within the DevSecOps workflow.
• Create guidelines for evaluating AI model effectiveness, usability, and productivity impact.

Tools

Python

Golang

Rust

TensorFlow

PyTorch

LangChain

Kubernetes

Kubeflow

MLflow

GitLab CI

Terraform

Apache Kafka

Spark

RESTful APIs

Job description

Naval Group Far East is seeking an AI MLOps Engineer to accelerate AI-driven prototypes that boost developer productivity across our Software Factory. You will prototype, test MVPs, and iterate on AI use cases, including code generation, testing automation, and CI/CD integration.

The role requires deep MLOps and AI experimentation experience with a focus on rapid deployment, collaboration with DevSecOps teams, and producing scalable solutions for production environments.