Job Description
Our Client
Our client is a global leader in cutting-edge technology and innovation, dedicated to transforming the software development landscape. They are at the forefront of integrating AI-driven solutions to enhance developer productivity and streamline the software lifecycle. With a focus on building and maintaining an advanced internal Software Factory, they are seeking a dynamic ML DevOps Engineer to join their forward-thinking team. This is a unique opportunity to work on high-impact AI use cases and shape the future of software development.
Job Responsibilities
As an ML DevOps Engineer, you will play a pivotal role in revolutionising software development processes by leveraging AI and machine learning. Your key responsibilities will include:
AI Use Case Development and Prototyping
- Rapidly developing and iterating on AI-driven prototypes to enhance developer workflows, including code specification, generation, and testing automation.
- Collaborating with product and DevSecOps teams to identify and implement high-impact AI use cases.
- Driving proof of concept (PoC) initiatives to transform experimental AI ideas into scalable solutions.
- Automating repetitive tasks in the development pipeline, such as auto-code generation and intelligent error detection.
MVP Development and Iterative Testing
- Building Minimum Viable Products (MVPs) for AI solutions, focusing on quick deployment and user feedback.
- Establishing testing frameworks to evaluate AI models and iterating on improvements.
- Integrating AI-based prototypes into the broader software lifecycle and measuring their impact.
End-to-End ML Pipeline Development
- Designing and deploying scalable ML pipelines with robust training, testing, deployment, and monitoring processes.
- Managing model versioning, retraining, and performance tracking to ensure high-quality AI solutions.
- Developing tools for A/B testing, canary releases, and other ML model rollout techniques.
Collaboration with DevSecOps Team
- Working closely with DevSecOps engineers to integrate ML workflows with existing CI/CD pipelines.
- Enhancing security measures for ML processes in compliance with DevSecOps protocols.
- Automating workflows to ensure faster, reliable, and secure model deployments.
Documentation and Compliance
- Documenting AI use cases, PoCs, MVPs, and best practices for AI integration within DevSecOps workflows.
- Creating guidelines for evaluating AI model effectiveness and productivity impact.
Ideal Talent
We are looking for an innovative and entrepreneurial professional with the following qualifications and skills:
Education and Experience
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s degree preferred).
- 3+ years of experience in MLOps, DevOps, or AI experimentation, with a focus on rapid prototyping and MVP development.
- Strong understanding of DevSecOps practices, tools, and methodologies.
Technical Skills
- Proficiency in Python, Golang, Rust, or other relevant programming languages.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch, LangChain), deployment platforms (e.g., Kubernetes), and ML pipeline tools (e.g., Kubeflow, MLflow).
- Familiarity with CI/CD tools (e.g., GitLab CI) and infrastructure-as-code (IaC) tools like Terraform.
- Knowledge of data pipelines and tools (e.g., Apache Kafka, Spark).
- Understanding of machine learning concepts, including neural networks and optimisation algorithms.
- Experience with Retrieval Augmented Generation (RAG) techniques and prompt engineering strategies.
Soft Skills
- Strong problem-solving skills and an innovative mindset.
- Excellent collaboration and communication skills to work across multidisciplinary teams.
- Self-driven, adaptable, and capable of managing multiple AI-driven projects in a dynamic environment.
Day-to-Day
- Collaborate with cross-functional teams to identify and implement AI-driven solutions.
- Develop and test prototypes, transforming innovative ideas into scalable solutions.
- Automate workflows to enhance developer productivity and streamline software delivery.
- Monitor and optimise ML pipelines, ensuring high performance and reliability.
- Document processes, share best practices, and contribute to a culture of continuous improvement.
Benefits
- Be at the forefront of AI innovation in software development.
- Work in a dynamic, fast-paced environment that values creativity and experimentation.
- Collaborate with a team of forward-thinking professionals.
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
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