We are seeking a highly skilled and innovative Machine Learning (ML) Lead with an entrepreneurial mindset, capable of thriving in a dual role as an individual contributor (IC) and team leader. The ideal candidate will spearhead ML initiatives, drive innovation, and establish a new ML team while fostering a culture of mentorship and collaboration. This role also involves exploring and working on regulatory technology (RegTech) solutions, delivering impactful ML-driven systems, and taking ownership of projects from conception to deployment.

Key Responsibilities:

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.

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.

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.

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.

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.

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 Lead, 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:

Education and Experience

- Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related field (PhD preferred).

- 7+ 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+ years of team management or mentorship experience, with a proven ability to grow teams.

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.