This role is for one of the Weekday's clients Salary range: Rs 2000000 - Rs 6000000 (ie INR 20- 60 LPA) Min Experience: 5+ years Location: India JobType: full-time We are seeking an experienced Senior AI/ML Engineer to join our growing technology team and drive the development of intelligent, data-driven solutions that solve complex business challenges.
This role is ideal for professionals who are passionate about building production-grade Artificial Intelligence and Machine Learning systems while working on large-scale enterprise applications.
You will collaborate with cross-functional teams including data scientists, software engineers, product managers, and business stakeholders to design, develop, deploy, and optimize AI-powered products that deliver measurable business value.
As a Senior AI/ML Engineer, you will play a key role in the end-to-end AI lifecycle—from data preparation and model development to deployment, monitoring, and continuous improvement.
You will contribute to architectural decisions, mentor junior engineers, and ensure AI solutions are scalable, secure, and aligned with business objectives.
Candidates with exposure to financial services, particularly banking and credit risk domains, will have an added advantage.
Key Responsibilities Design, build, and deploy scalable Artificial Intelligence and Machine Learning solutions for real-world business problems.
Develop, train, evaluate, and optimize machine learning models using structured and unstructured data.
Build robust data pipelines for feature engineering, model training, validation, and inference.
Deploy ML models into production environments and monitor performance, scalability, and reliability.
Collaborate with engineering teams to integrate AI capabilities into enterprise applications and APIs.
Evaluate new AI techniques, frameworks, and technologies to improve solution effectiveness.
Implement model monitoring, retraining strategies, and MLOps best practices for production systems.
Work closely with product managers and business stakeholders to translate business requirements into AI-driven solutions.
Mentor junior engineers by conducting code reviews and sharing best practices in AI and software engineering.
Ensure compliance with security, governance, and responsible AI principles throughout the development lifecycle.
Required SkillsMust-Have Skills Strong expertise in Artificial Intelligence concepts, algorithms, and modern AI frameworks.
Hands-on experience in Machine Learning , including supervised and unsupervised learning techniques.
Proficiency in Python and popular ML libraries such as TensorFlow, PyTorch, Scikit-learn, XGBoost, or similar.
Experience with feature engineering, model optimization, hyperparameter tuning, and performance evaluation.
Strong understanding of deep learning, NLP, computer vision, or generative AI concepts.
Experience building scalable AI applications using cloud platforms and containerized environments.
Familiarity with REST APIs, microservices architecture, and software engineering best practices.
Strong knowledge of SQL, data processing frameworks, and distributed computing concepts.
Experience with version control systems, CI/CD pipelines, and MLOps tools.
Good-to-Have Skills Domain knowledge in Wholesale Banking processes and enterprise financial workflows.
Understanding of Corporate Banking products, lending operations, and financial data ecosystems.
Experience developing AI solutions for Credit Risk assessment, underwriting, fraud detection, or risk analytics.
Familiarity with regulatory compliance, explainable AI, and model governance in financial institutions.
Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related discipline.
5–9 years of professional experience in AI/ML engineering, software development, or data science.
Experience delivering AI solutions in production environments with measurable business impact.
Strong analytical thinking, problem-solving, and communication skills.
Ability to work effectively in agile, collaborative, and fast-paced development environments.
