Machine Learning lead
6 days ago
Job Description: ML Lead (Individual Contributor and Team Management)
Experience: Minimum 7 years and above
Permanent Role
Position Overview
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
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 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
1. Education and Experience
○ Bachelor’s or Master’s 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.
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 the ability to take initiative.
○ Exceptional communication skills for both technical and non-technical stakeholders.
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