AI ML Engineer
TECH AALTO PTE. LTD.
- Education: Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline.
- Experience: 5 years of hands-on experience building and deploying ML/AI applications. This must include at least one LLM-enabled system delivered beyond prototype into operational use.
Technical & Professional Competencies
- Strong Python software engineering capability, including API development, testing, version control and modular system design.
- Hands-on experience building and deploying ML/AI applications, including at least one LLM-enabled or agentic AI solution beyond proof-of-concept stage.
- Experience with LLM applications, retrieval, tool use, workflow orchestration or multi-agent frameworks such as LangGraph, CrewAI or equivalent.
- Experience integrating AI/ML solutions with enterprise data platforms, databases, APIs or cloud services.
- Ability to design and implement systematic evaluation frameworks for AI systems, including testing, benchmarking, observability and reproducibility.
- Working knowledge of AI governance, security and Responsible AI practices, including human-in-the-loop controls, access management, auditability and safeguards against misuse.
- Strong problem-solving and analytical skills, with the ability to translate business requirements into scalable AI-enabled solutions. Preferred (Advantageous)
- Experience with AWS services such as Bedrock, Redshift, Glue, S3, Lambda or related cloud-native services.
- Experience with PySpark, Databricks or large-scale data processing and feature engineering pipelines.
- Experience with CI/CD, containerisation, MLOps or model deployment tooling (e.g. Docker, MLflow, GitHub Actions, Jenkins).
- Experience implementing monitoring, observability and operational support processes for ML/AI applications.
- Experience delivering fraud detection, risk, compliance, investigation or decision support solutions.
- Experience with knowledge retrieval, RAG, graph-based workflows, prompt management, model evaluation tooling or AI observability platforms.
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