Machine Learning Engineer - Fresher

Responsibilities:

• Design, develop, and deploy scalable machine learning models for wealth management use cases such as portfolio optimisation, investment recommendations, client segmentation, risk profiling, and financial forecasting.
• Build and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
• Develop AI/LLM-based solutions for financial research, document intelligence, and advisor productivity.
• Collaborate with product, engineering, and investment teams to translate business problems into data-driven solutions.
• Ensure production-grade ML systems with a focus on scalability, explainability, performance, and reliability.
• Evaluate emerging AI/ML techniques and drive innovation across financial products.

Requirements:

• Bachelors, Masters, or PhD in Computer Science, Artificial Intelligence, Mathematics, Statistics, Electrical Engineering, or a related quantitative discipline.
• Preferred candidates from premier institutes such as IITs, IISc, ISI, BITS Pilani, IIITs, or globally recognised universities.
• 0-3 years of experience building and deploying production-grade machine learning solutions, preferably in wealth management, financial services, fintech, or other data-intensive domains.

Expertise Required:

• Strong foundation in machine learning, deep learning, probability, statistics, linear algebra, and optimisation.
• Hands-on experience with Python, SQL, PyTorch/TensorFlow, Scikit-learn, and ML frameworks.
• Experience with time-series forecasting, recommendation systems, NLP/LLMs, and MLOps.
• Proficiency with cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, Git, and CI/CD pipelines.
• Familiarity with financial markets, portfolio analytics, risk modelling, or quantitative finance is highly desirable.
• Excellent problem-solving skills with the ability to build scalable, production-ready AI systems and translate research into business impact.