1. Machine Learning Development ○ Design, develop, and deploy machine learning models for diverse use cases, including RegTech applications, predictive analytics, natural language processing, and computer vision. ○ Drive innovation by experimenting with cutting-edge algorithms and frameworks to solve challenging problems. ○ Optimize models for scalability, performance, and real-time deployment. 2. ML Operations (MLOps) ○ Build and manage end-to-end ML pipelines, encompassing data collection, preprocessing, model training, deployment, and monitoring. ○ Implement MLOps best practices, including CI/CD pipelines, model versioning, and production monitoring. ○ Ensure robustness and scalability of deployed models, enabling consistent performance in production environments. 3. Team Leadership and Mentorship ○ Build and lead a high-performing ML team from scratch, defining team goals and fostering a culture of collaboration and innovation. ○ Act as a mentor, guiding team members on technical challenges, career development, and industry best practices. ○ Inspire and motivate the team to take ownership and excel in their roles. 4. Initiative and Innovation ○ Take proactive ownership of projects, identifying opportunities to create value through ML-driven solutions. ○ Explore and develop innovative ML approaches tailored to regulatory technology (RegTech) challenges and compliance requirements. ○ Stay updated with industry trends and emerging technologies to drive forward-thinking solutions. 5. Cross-Functional Collaboration ○ Partner with product managers, engineers, and stakeholders to align ML projects with business and compliance goals. ○ Translate complex regulatory requirements into technical solutions that ensure accuracy, scalability, and compliance. 6. Research and Documentation ○ Conduct research to advance the application of ML in RegTech and other key domains. ○ Document models, pipelines, and processes to ensure clarity, reproducibility, and knowledge sharing. ○ Present findings and progress to stakeholders and leadership effectively. Challenges We Are Tackling As an ML Engineer , you will work on solving some of the most critical and impactful challenges, including: ● Identity Fraud Detection: Leveraging ML to detect and prevent fraudulent activities in AML, identity document tampering and face biometrics ● Intelligent Document Processing: Building systems to extract, classify, parse, and analyze information from complex documents with high accuracy and scalability to automate various processes in Fintech and other industries. ● Motor Insurance & Finance: Developing ML-driven solutions for policy generation, Fraud Prevention, automating vehicle claims processing, minimizing delays, and improving accuracy. ● Contract Lifecycle Management: Leveraging Natural Language Processing (NLP) to streamline and enhance the management of legal contracts, including tasks like automated clause extraction, compliance checks, and contract analytics. ● User Knowledge Graph: Leveraging Graph Databases and anomaly detection to provide actionable insights into user behavior, generate trust scores for users and their associated documents, and enhance decision-making for personalized and secure services. Key Qualifications 1. Education and Experience ○ Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (PhD preferred). ○ 4+ years of experience in ML/AI, with a strong track record of successful model deployments. ○ Preferred experience in RegTech/Fintech or an interest in applying ML in Fintech solutions. 2. Technical Skills ○ Expertise in ML frameworks and tools. ○ Strong understanding of MLOps platforms (e.g., MLflow, Kubeflow) and cloud infrastructure (AWS, GCP, Azure). ○ Proficiency in Python, and experience with big data tools (e.g., Spark, Hadoop). ○ Familiarity with regulatory and compliance systems is a plus. ○ Working with unstructured document information is nice to have. 3. Soft Skills ○ Innovation-driven mindset with a passion for tackling complex challenges. ○ Strong leadership, mentoring, and team-building skills. ○ Excellent problem-solving abilities and an ability to take initiative. ○ Exceptional communication skills for both technical and non-technical stakeholders.

About Quickhyre AI

QuickHyre AI is an online job portal and HRMS software platform for hiring and workforce management, trusted by over 10 million active users. It connects freshers and experienced professionals across all career levels with verified job opportunities, while enabling companies to hire, onboard, and manage employees through a single system. Candidates use QuickHyre AI to search and apply for jobs across entry-level, mid-level, and senior roles, including internships and contract positions across tech and non-tech domains. Employers use QuickHyre AI as a hiring platform, applicant tracking system (ATS), and HRMS to post jobs, screen candidates, manage applications, onboard hires, and maintain employee records. Built for startups, growing companies, and enterprises, QuickHyre AI reduces irrelevant applications, improves hiring efficiency, and simplifies HR operations. By combining job discovery, online recruitment, and HR management software, QuickHyre AI supports end-to-end talent acquisition and workforce administration at scale.