Job Title: Senior AI / Machine Learning Engineer

​

Location:Hyderabad (Hybrid / Onsite)

Experience: 3–7 Years

Industry: Financial Services / FinTech

Employment Type: Full-time

​

About the Role

​

We are looking for a highly skilled AI / Machine Learning Engineer to design, build, and scale intelligent data-driven solutions for complex financial use cases. This role will work closely with product, engineering, and business stakeholders to develop models that power risk, fraud, personalization, forecasting, and decision intelligence across financial platforms.

​

You will be part of a fast-paced, innovation-driven environment where AI is core to business outcomes—not an experimental add-on.

​

Key Responsibilities

​

\* Design, develop, and deploy machine learning models for real-world financial problems such as fraud detection, credit risk, pricing, recommendations, and customer intelligence

\* Work on end-to-end ML lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring

\* Build scalable ML pipelines using Python and modern ML frameworks

\* Collaborate with data engineers to process large structured and unstructured datasets

\* Apply statistical modeling, supervised/unsupervised learning\*\*, and optimization techniques

\* Ensure model explainability, fairness, and compliance (especially for regulated financial environments)

\* Continuously improve model performance through experimentation and A/B testing

\* Contribute to ML best practices, code reviews, and technical documentation

​

Required Skills & Qualifications

​

\* 3+ years of hands-on experience in Machine Learning / AI roles

\* Strong programming experience in Python

\* Solid understanding of ML algorithms, statistics, probability, and linear algebra

\* Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost\*\*

\* Hands-on experience with SQL and data analysis

\* Familiarity with cloud platforms (AWS / Azure / GCP) and ML deployment workflows

\* Experience working with large-scale datasets and real-time or batch ML systems

​

​

Preferred / Good-to-Have

​

\* Prior experience in financial services, banking, lending, insurance, payments, or fintech

\* Knowledge of fraud analytics, risk modeling, credit scoring, or time-series forecasting

\* Experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes)

\* Understanding of model governance, explainable AI (XAI), and regulatory constraints

\* Exposure to NLP or Deep Learning use cases

​

What We Offer

​

\* Opportunity to work on high-impact AI systems used at scale

\* Exposure to complex financial datasets and decision systems

\* Competitive compensation and performance-linked growth

\* Strong learning culture with access to advanced tools and platforms

\* Collaborative, outcome-driven engineering environment

​

Who Should Apply

​

If you are passionate about applying AI and Machine Learning to solve real financial problems, enjoy working on production-grade ML systems, and want your models to influence critical business decisions—this role is for you.

​

​