Principal, Machine Learning Engineer (L5)

<h3>Accountabilities</h3><li>
<strong>Lead AI/ML innovation:</strong>Design, develop, and deliver advanced machine learning capabilities for intelligent customer engagement, supporting new functionality within a rapidly evolving product environment.</li><li>
<strong>Drive research and experimentation:</strong>Translate ambiguous business and technical challenges into structured research initiatives, design rigorous experiments, and validate hypotheses through rapid development cycles.</li><li>
<strong>Advance LLM and contextual intelligence capabilities:</strong>Investigate and implement state-of-the-art LLM orchestration, embedding models, retrieval strategies, vector stores, and data-driven personalization techniques.</li><li>
<strong>Build production-grade ML systems:</strong>Architect, develop, and deploy scalable machine learning services capable of processing high-volume data and supporting streaming and real-time inference workloads.</li><li>
<strong>Establish technical excellence:</strong>Define architectural standards, engineering best practices, and design principles that improve system reliability, maintainability, performance, and scalability.</li><li>
<strong>Provide technical leadership and mentorship:</strong>Guide engineers through technical reviews, architectural decisions, knowledge sharing, and mentoring, raising the team's capabilities without requiring formal management authority.</li><li>
<strong>Leverage modern AI development tools:</strong>Identify and integrate emerging AI frameworks and development platforms to accelerate implementation, reduce repetitive engineering work, and focus resources on high-value innovation.</li><li>
<strong>Collaborate across teams:</strong>Work closely with cross-functional stakeholders to translate complex requirements into effective technical solutions and communicate research findings, trade-offs, and implementation strategies.</li><li>
<strong>Continuously evolve technical expertise:</strong>Stay informed about advances in machine learning, generative AI, autonomous agents, and personalization, applying relevant developments to real-world product challenges.</li><h2>Requirements</h2><li>
<strong>Professional experience:</strong>At least 10 years of applied machine learning or artificial intelligence experience, with a proven track record of independently owning technically ambitious systems from conception through production deployment.</li><li>
<strong>Technical leadership:</strong>Demonstrated ability to operate in ambiguous, early-stage product environments, take initiative, make informed decisions, and deliver results without waiting for fully defined requirements.</li><li>
<strong>Programming expertise:</strong>Strong proficiency in Python and experience developing robust, maintainable software for complex machine learning applications.</li><li>
<strong>Machine learning foundations:</strong>Deep understanding of statistical machine learning algorithms, transformer architectures, large language models, and modern AI techniques.</li><li>
<strong>Production AI/ML architecture:</strong>Extensive experience designing, architecting, and deploying production-grade AI/ML systems, including LLM orchestration, embedding models, and vector databases.</li><li>
<strong>Cloud engineering:</strong>Hands-on experience building cloud-based services on AWS, Google Cloud Platform (GCP), or Microsoft Azure.</li><li>
<strong>Data-intensive systems:</strong>Experience working with high-volume datasets, streaming pipelines, real-time inference systems, and diverse data storage technologies.</li><li>
<strong>Technical influence:</strong>Ability to elevate engineering standards through mentorship, design reviews, architectural guidance, and effective knowledge sharing.</li><li>
<strong>Communication and collaboration:</strong>Excellent communication skills, sound technical judgment, and the ability to work effectively with multidisciplinary and geographically distributed teams.</li><li>
<strong>Preferred experience:</strong>Previous work developing autonomous agents capable of managing multi-turn conversations while maintaining long-term context and consistency.</li><li>
<strong>Predictive modeling expertise:</strong>Experience modeling user behavior, designing experiments, and applying causal or counterfactual inference methods when full randomization is not possible.</li><li>
<strong>Global collaboration:</strong>Experience working within distributed teams across different locations and time zones.</li><h2>Benefits</h2><li>Competitive compensation aligned with experience, skills, and local market conditions.</li><li>Remote-first working arrangements for eligible employees based in India.</li><li>Generous paid time off to support rest, personal commitments, and work-life balance.</li><li>Parental leave and additional wellness leave.</li><li>Healthcare benefits, with specific offerings depending on location.</li><li>Retirement savings programs, subject to local eligibility and plan availability.</li><li>Opportunities to work on advanced AI/ML technologies and solve complex, large-scale engineering challenges.</li><li>A collaborative, globally distributed environment that encourages innovation, continuous learning, and professional growth.</li><li>Opportunities to influence technical strategy, mentor talented engineers, and contribute to high-impact AI-powered products.</li><li>Support for employee volunteering and charitable giving initiatives.</li><li>Occasional travel for team gatherings, customer meetings, and in-person collaboration may be required.</li>