ML/AI Engineer: LLMOps & Predictive Analytics

Avanade; Kuala Lumpur; On-site; MYR 180,000 - 260,000; Full time

Job summary

Avanade is seeking an experienced ML/AI Engineer to design and deploy scalable ML solutions, with hands-on work in LLMOps, deep learning and statistical modeling. You will join the Data & AI team to build analytics solutions for clients and translate complex data into actionable insights.

You will collaborate with teammates to define use cases, transform prototypes into production systems, and optimize ML libraries while delivering measurable business impact across industries.

Qualifications

• 5+ years deploying ML solutions on Azure platforms.
• Experience in data analytics, BI and data warehousing.
• Hands-on with MLOps frameworks and model deployment.
• Familiar with structured and unstructured data, streaming, NLP.
• Knowledge of neural networks and transformer models.

Responsibilities

• Design ML systems and AI software to automate predictive models.
• Prepare advanced data analyses and present results to stakeholders.
• Define Data Science use cases with current technologies.
• Transform data science prototypes into deployable ML solutions.
• Auto-tag images and perform text-to-speech conversions on unstructured data.
• Optimize ML libraries and frameworks for performance.
• Develop ML algorithms to analyze large historical datasets for predictions.
• Run tests, perform statistical analysis, and interpret results.

Skills

5+ years ML deployment

Data analytics & BI

MLOps frameworks

Structured & unstructured data

Neural networks & transformers

Tools

Azure ML

MLOps tools

Job description

Avanade is seeking an experienced ML/AI Engineer to design and deploy scalable ML solutions, with hands-on work in LLMOps, deep learning and statistical modeling. You will join the Data & AI team to build analytics solutions for clients and translate complex data into actionable insights.

You will collaborate with teammates to define use cases, transform prototypes into production systems, and optimize ML libraries while delivering measurable business impact across industries.