Overview

Company Description

Responsibilities

• ABOUT IQ-EQ
• We’re a leading Investor Services group offering end-to-end services in administration, accounting, reporting, regulatory and compliance needs of the investment sector worldwide.  We employ a global workforce of 6,500+ people across 24 jurisdictions and have assets under administration (AUA) exceeding US$857 billion. We work with 13 of the world’s top-15 private equity firms.
• Our services are underpinned by a Group-wide commitment to ESG and best-in-class technology including a global data platform and innovative proprietary tools supported by in-house experts.
• Above all, what makes us different is our people. Operating as trusted partners to our clients, we deliver intelligent solutions through a combination of technical expertise and strong relationships based on deep client understanding.
• We’re driven by our Group purpose, to power people and possibilities.
• Introduction
• You'll design, develop, deploy, and optimize production-grade machine learning, deep learning, NLP, computer vision, recommendation, classification, and predictive analytics solutions, including foundation model fine-tuning and evaluation.
• You'll architect and build advanced Generative AI applications using LLMs, RAG, vector databases, Agentic AI frameworks, multi-agent systems, workflow orchestration, prompt engineering, function calling, and enterprise tool integrations.
• You'll develop scalable ML pipelines and AI platforms by performing data preparation, feature engineering, model training, validation, monitoring, inference optimization, and lifecycle management.
• You'll implement robust MLOps, cloud, and DevOps practices, including CI/CD pipelines, experiment tracking, model registries, automated retraining, containerization with Docker and Kubernetes, and deployment across Azure, AWS, and GCP.
• You'll translate business requirements into scalable AI products, design reusable AI services and APIs, drive technical architecture decisions, and ensure AI governance, security, observability, compliance, and responsible AI standards.

Qualifications

• You have 7-10+ years of experience in AI/ML engineering, data science, or related fields, and hold a bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related discipline.
• You possess expert-level proficiency in Python and strong experience with SQL and preferably Java or C#, along with hands-on expertise in machine learning and deep learning frameworks such as Scikit-learn, XGBoost, LightGBM, TensorFlow, and PyTorch.
• You have deep experience building Generative AI solutions using OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Llama models, RAG architectures, vector databases, and AI frameworks including LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, and LlamaIndex.
• You are experienced in data engineering, MLOps, and cloud-native development, with strong knowledge of Pandas, NumPy, Spark/PySpark, MLflow, Kubeflow, Azure ML, SageMaker, Airflow, Azure, AWS, GCP, Docker, Kubernetes, Terraform, GitHub Actions, and Azure DevOps.
• You demonstrate strong leadership, problem-solving, communication, and collaboration skills, with expertise in enterprise-scale AI solutions, distributed systems, microservices, Responsible AI, AI security, observability, governance, and emerging technologies such as Agentic AI, Microsoft Copilot, Fabric, OneLake, and Azure AI Services.

Benefits

• Competitive Compensation: Annual package including base salary, allowances, and performance incentives.
• Health & Insurance Coverage: Medical insurance, group term life insurance, and accident coverage.
• Allowances & Support: Transportation allowance, internet allowance, and shift allowance.
• Paid Time Off: Generous leave policy supporting work–life balance.
• Career Growth: Exposure to cutting‑edge AI/ML technologies and opportunities to work across Generative AI, MLOps, and cloud‑native solutions.