Job Summary
We are looking for a highly experienced AI/ML Engineer with 8+ years of hands-on experience designing, developing, deploying, and supporting enterprise-grade Machine Learning and AI solutions. The ideal candidate will have strong expertise in Python, Machine Learning, Generative AI, LLMs, NLP, and cloud-based AI platforms, with proven experience taking models and AI solutions from development through production.
Experience working within the Banking, Financial Services, or FinTech domain is highly preferred, particularly in areas such as fraud detection, risk management, credit analytics, customer intelligence, AML, or financial forecasting.
Key Responsibilities
- Design, develop, and implement end-to-end AI/ML solutions for complex business problems.
- Develop and productionize machine learning models using Python, Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
- Build and deploy Generative AI, LLM, NLP, and RAG-based solutions for enterprise use cases.
- Work hands-on with LLMs, prompt engineering, embeddings, vector databases, and AI agents.
- Develop scalable ML pipelines covering data preparation, feature engineering, model training, validation, deployment, and monitoring.
- Deploy AI/ML models into production environments using AWS, Azure, or GCP.
- Build and maintain MLOps pipelines for model deployment, versioning, monitoring, and continuous improvement.
- Integrate AI/ML models with enterprise applications through REST APIs, microservices, and cloud-native architectures.
- Collaborate closely with data engineers, software engineers, architects, product teams, and business stakeholders.
- Analyze large and complex datasets to identify patterns, trends, anomalies, and actionable insights.
- Optimize model performance, scalability, reliability, and cost for production workloads.
- Implement appropriate practices around model governance, explainability, security, data privacy, and responsible AI.
- Troubleshoot and enhance existing AI/ML applications and production models.
- Stay current with emerging developments in Generative AI, Agentic AI, LLMs, foundation models, and ML technologies.
Required Skills & Experience
- 8+ years of hands-on experience in AI/ML engineering, Machine Learning, Data Science, or related areas.
- Strong hands-on programming experience with Python.
- Strong understanding of Machine Learning algorithms, statistical modeling, feature engineering, and model evaluation.
- Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or equivalent ML frameworks.
- Hands-on experience building and deploying Generative AI / LLM applications.
- Experience with RAG, embeddings, vector databases, prompt engineering, and LLM orchestration frameworks.
- Strong experience with NLP, classification, regression, clustering, anomaly detection, or recommendation systems.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Hands-on experience with Docker, Kubernetes, CI/CD, and MLOps practices.
- Strong knowledge of SQL and data processing technologies.
- Experience developing REST APIs and production-grade AI/ML services.
- Strong understanding of software engineering principles, Git, testing, debugging, and production support.
Preferred Qualifications
- Banking, Financial Services, FinTech, or Insurance domain experience preferred.
- Experience with banking use cases such as Fraud Detection, AML, Transaction Monitoring, Credit Risk, Customer Segmentation, Risk Analytics, or Financial Forecasting.
- Experience with AWS Bedrock, Azure OpenAI, OpenAI APIs, Vertex AI, or similar enterprise AI platforms.
- Experience building AI agents / Agentic AI solutions.
- Experience with LangChain, LangGraph, LlamaIndex, MLflow, Kubeflow, or similar technologies.
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Mathematics, or a related field.
- Strong communication and stakeholder management skills.