AI Engineer

Overview

Our Client is looking for a skilled and motivated AI Engineer with 2–3 years of hands-on experience to design, build, and deploy AI/ML solutions that solve real-world operational and data challenges. The role involves working closely with data, technology, and domain experts to deliver production-grade AI use cases.

Key Responsibilities

• Design, develop, and deploy AI/ML models for operational and data-driven use cases.
• Work on end-to-end ML pipelines, including data ingestion, preprocessing, model training, evaluation, and deployment.
• Implement Applied AI solutions (e.g., NLP, predictive analytics, automation, anomaly detection) aligned with business needs.
• Collaborate with data engineers, product teams, and domain experts to translate requirements into scalable AI solutions.
• Optimise model performance, scalability, and reliability in production environments
• Document models, workflows, and technical designs clearly
• Stay updated with emerging AI/ML techniques and recommend practical adoption
  
  

• 2–3 years of experience in AI/ML engineering or data science roles
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Langchain and Langraph
• Solid understanding of machine learning algorithms, statistics, and data modelling
• Experience working with structured and unstructured data
• Familiarity with SQL and data processing tools
• Exposure to cloud platforms (AWS, Azure, or GCP) is a plus
• Understanding of model deployment, APIs, and basic MLOps concepts
• Experience with NLP, LLMs, or GenAI use cases
• Hand-on experience in
• Knowledge of data engineering tools (Spark, Airflow, Databricks, etc.)
• Exposure to financial services, asset management, or alternative assets
• Experience in automation, workflow optimization, or operational analytics
• Familiarity with Docker, CI/CD pipelines, or MLOps tools