ML Manager

Role Overview: As a fintech company where Machine Learning (ML) is a key driver of impact, ensuring the building and deployment of state-of-the-art ML capabilities is critical. Your role will involve transforming ML models into high-performance production-level code, implementing sophisticated machine learning algorithms, robustness monitoring, system logging/alarming, and DevOps. This position will be hybrid from our Bengaluru office, offering excellent employee benefits such as healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with teams in our Palo Alto HQ and Bangkok Site. Key Responsibilities: - Lead a team of Machine Learning Engineers and ML Analysts to drive core ML initiatives with multimodal data streams - Review designs and launch efficient, reliable models for business impact - Find innovative solutions to key problems and deliver high-quality code - Collaborate with cross-functional teams to take products to market - Train and deploy state-of-the-art multi-task deep learning and/or statistical model pipelines - Develop a deep understanding of applications and the rationale behind models & systems - Partner with stakeholders to analyze business problems and define system requirements - Work with data platform teams to enable robust, scalable data pipelines - Drive high engineering standards through mentoring and knowledge-sharing - Promote engineering best practices including code reviews, automated testing, and monitoring Qualifications Required: - 8+ years of ML engineering experience with extensive knowledge of machine learning algorithms - 4+ years of experience managing and leading a team of ML Engineers driving product initiatives - Bachelor's or Masters degree in Computer Science, Engineering, or related field - 4+ years of experience collaborating closely with product, analytics, and engineering teams - Hands-on experience with architectural patterns for high-scale software applications - Industry experience in building and productionizing machine learning systems - Strong oral and written communication skills,