AI / ML Engineer at Contec Global Infotech Limited

Job Summary

• As a Mid-Level AI/ML Engineer, you will design, develop, and deploy machine learning models to solve real-world problems in fraud detection, credit scoring, transaction monitoring, and customer personalization.
• You’ll work closely with data engineers, backend developers, and product teams to translate business needs into AI-driven solutions that scale.

Key Responsibilities

• Conduct exploratory data analysis, feature engineering, and statistical analysis to uncover patterns and improve model accuracy.
• Handle data cleaning, preprocessing, and managing imbalanced/complex Fintech datasets.
• Design and analyze experiments (e.g., A/B testing) to validate model business impact.
• Develop, train, and deploy ML models for fraud detection, risk assessment, credit scoring, and personalization.
• Collaborate with DevOps team to ensure high-quality, reliable data pipelines for ML workloads.
• Optimize models for performance, scalability, and low latency in production fintech environments.
• Implement explainable AI (XAI) techniques to ensure model transparency and compliance with financial regulations.
• Continuously monitor and improve deployed models with real-time data feedback loops.
• Contribute to the design of APIs for model inference and integration into core fintech applications.
• Stay updated with emerging AI/ML techniques, especially in the financial domain (graph ML, anomaly detection, NLP for KYC, etc.).

Requirements

• Education: Bachelor’s or Master's in Computer Science, Data Science, Engineering, or related field.
• Experience: 3–5 years of experience in AI/ML engineering, preferably in FinTech, banking, or payments.

Technical Skills:

• Deep knowledge of statistics, hypothesis testing, and classical ML algorithms.
• Strong programming skills in Python (Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow).
• Proficiency in tools such as Jupyter Notebooks and in data visualization libraries e.g Matplotlib and Seaborn.
• Experience with SQL and working knowledge of big data tools (Spark, Dask, or similar).
• Hands-on experience deploying ML models via APIs, Docker, or cloud platforms (e.g AWS/GCP/Azure/Huawei).
• Familiarity with real-time systems (Kafka, NATS, or streaming pipelines) is a plus.
• Knowledge of fraud detection, anomaly detection, or credit risk models in fintech.
• Experience with process orchestration tools such as Prefect or Airflow is an advantage.
• Knowledge of regulatory compliance frameworks (e.g. PCI DSS, NDPR etc.).

Soft Skills:

• Strong problem-solving and analytical mindset.
• Ability to work in a fast-paced startup environment.
• Effective communicator and collaborator with cross-functional teams.

Nice to Have:

• Exposure to MLOps tools (MLflow, Kubeflow, or SageMaker).
• Knowledge of AI Orchestration framework (e.g. LangChain, Haystack).
• Experience with AI/Automation tools such as n8n and Zapier.