Lead Machine Learning Engineer

Location: On-Site Virtuosoft Pvt. Ltd Team: Data Science and Machine Learning About the Role: We are looking for an exceptional Lead Machine Learning Engineer to join our forward-thinking Data Science and Machine Learning team. This is an exciting opportunity to lead the development of cutting-edge data-driven services that will transform the financial services landscape. You will take charge of a talented team, working on innovative products that leverage advanced machine learning techniques to deliver high-impact solutions. If you have a passion for building scalable, production-ready ML systems and thrive in an agile, fast-paced environment, we want to hear from you! What You Will Do: Lead the Team: Act as the technical lead for a dynamic team of Machine Learning Engineers and Data Scientists, guiding the development of core capabilities for our Insights products. Design and Implement: Architect and implement high-performance financial data enrichment services that support banking, Fintech, and lending sectors. Drive Technical Strategy: Contribute to the technical roadmap, defining strategies for scaling services and delivering innovative solutions. Solve Complex Challenges: Apply cutting-edge NLP and machine learning techniques to extract actionable insights from financial data, solving real-world problems such as transaction categorization and merchant name recognition. Collaborate and Innovate: Work closely with cross-functional teams, including Product, Data Platform, and DevOps, to create world-class solutions. Own MLOps Lifecycle: Take responsibility for the full MLOps lifecycle—prototyping, developing, deploying, and monitoring machine learning models and services. Foster an Agile Culture: Promote agile practices, ensuring collaboration, empowerment, and mission-driven work across the team. Your Profile: Extensive ML Experience: You have a proven track record of designing, building, and deploying machine learning models at scale, using frameworks such as TensorFlow, PyTorch, and Scikit-learn. MLOps Expertise : You are well-versed in MLOps practices, including model versioning, CI/CD pipelines, and cloud-based deployment automation. NLP Proficiency: You possess deep knowledge of NLP techniques, including text pre-processing, semantic extraction, and leveraging libraries like spaCy and transformers. Cloud & Microservices Experience: Familiar with deploying real-time ML systems on cloud platforms, and working with microservices and containerization technologies like Kubernetes. Strong Communication Skills : You are adept at conveying complex technical concepts to both technical and non-technical stakeholders, ensuring alignment across teams. Team-Oriented Leadership: A collaborative leader with a passion for mentoring and building a high-performing, empowered data organisation. Experience:

• Minimum 5+ years of experience in building and deploying machine learning models in a production environment.
• Proven experience leading a team of machine learning engineers and data scientists, taking ownership of complex projects from design to deployment.
• Hands-on experience with machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Expertise in implementing and scaling machine learning solutions in real-time systems and cloud environments.
• Experience in designing and implementing natural language processing (NLP) models and techniques.

• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related field. Master’s degree required.
• Previous experience in Fintech or start-up environments is a strong advantage.
• Experience as a line manager is a bonus.