Ai Ml Engineer

Job Description AI/ML Engineer (5 Years Experience)

About Volante:
Volante is a leading Financial Services technology company providing a market-leading, cloud-native Payments Processing Platform to banks and financial institutions globally. By joining our product team, you will have an opportunity to shape the future of payments technology while working on cutting-edge AI/ML solutions.

Role Overview:
We are seeking an experienced AI/ML Engineer with ~5 years of hands-on experience in building, deploying, and scaling machine learning solutions. The ideal candidate will have strong expertise in Python, deep learning, generative AI, and end-to-end model deployment (cloud and on-premises), with exposure to the financial services domain.

Key Responsibilities:
- Design, build, and deploy ML/AI models for classification, prediction, NLP, and recommendation tasks. - Fine-tune large language models (LLMs) and deep learning models (TensorFlow, PyTorch). - Build scalable data pipelines using Python, SQL, and modern data frameworks. - Deploy ML models into production (on-premise and cloud) using Docker, Kubernetes, and MLflow. - Ensure robust monitoring, observability, and drift detection for deployed models. - Collaborate with cross-functional teams (Product, Engineering, Business) to identify AI/ML opportunities. - Ensure compliance with data privacy and security standards within financial services. - Mentor junior engineers and contribute to technical best practices. - Document development processes, results, and lessons learned for future reference.

Required Skills & Experience:
- Education: Bachelors or Master’s in Computer Science, Data Science, Machine Learning, or related field. - 5 years of experience in AI/ML engineering and applied machine learning. - Strong programming in Python (NumPy, Pandas, SciPy); R exposure is a plus. - Experience with ML/DL frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM. - Experience with Generative AI, LLM fine-tuning, and NLP pipelines. - Strong understanding of statistics, experimentation, and optimization techniques. - Hands-on experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. - Familiarity with financial services or payments industry preferred.

Desirable Skills:
- Exposure to cloud platforms (AWS, GCP, Azure). - Knowledge of compliance, data privacy regulations, and secure AI deployment. - Experience with MLOps tools (Airflow, MLflow, Optuna, monitoring dashboards such as Grafana).