Staff Machine Learning Engineer (L4)

<h3>Accountabilities</h3><li>
<strong>Build innovative AI/ML capabilities:</strong>Design, develop, and deploy new machine learning functionality that supports intelligent engagement, contextual understanding, and personalized customer experiences across digital communication channels.</li><li>
<strong>Lead end-to-end technical initiatives:</strong>Take ownership of technically ambitious projects, translating early-stage concepts and ambiguous requirements into robust solutions, from initial research and experimentation through production deployment.</li><li>
<strong>Design and execute experiments:</strong>Develop rigorous experiments to evaluate new ideas, test hypotheses, measure performance, and validate potential improvements, delivering actionable results within short development cycles.</li><li>
<strong>Advance LLM research and implementation:</strong>Investigate and apply state-of-the-art techniques in large language models, LLM orchestration, retrieval-augmented generation, and contextual intelligence to solve complex machine learning challenges.</li><li>
<strong>Develop scalable machine learning systems:</strong>Build and optimize production-grade ML services capable of supporting high-volume data processing, streaming workloads, real-time inference, and demanding enterprise requirements.</li><li>
<strong>Improve personalization and contextual intelligence:</strong>Develop capabilities that help applications and AI agents maintain relevant customer context, understand historical interactions, and deliver consistent, personalized experiences.</li><li>
<strong>Leverage modern AI development tools:</strong>Proactively evaluate and integrate emerging AI frameworks, development stacks, and automation tools to accelerate implementation and focus engineering effort on high-value product differentiation.</li><li>
<strong>Apply strong ML fundamentals:</strong>Use statistical machine learning, transformer architectures, predictive modeling, and other relevant techniques to develop effective solutions to complex data and personalization problems.</li><li>
<strong>Establish engineering best practices:</strong>Promote high standards for system architecture, code quality, experimentation, reliability, and maintainability through technical design reviews and engineering guidance.</li><li>
<strong>Mentor and support engineers:</strong>Share expertise, provide constructive feedback, and help teammates strengthen their technical capabilities without relying on formal managerial authority.</li><li>
<strong>Collaborate across functions:</strong>Work closely with product, engineering, and other stakeholders to align technical solutions with business objectives, communicate findings, and ensure successful delivery.</li><li>
<strong>Continuously explore new technologies:</strong>Stay informed about advances in AI, machine learning, and cloud engineering, rapidly acquiring new skills and applying relevant innovations to evolving product requirements.</li><li>
<strong>Contribute to distributed team execution:</strong>Coordinate effectively with colleagues across locations and time zones, maintaining clear communication and strong collaboration in a remote-first environment.</li><h2>Requirements</h2><li>
<strong>Extensive machine learning experience:</strong>At least 8 years of applied machine learning or artificial intelligence experience, with a demonstrated track record of independently owning technically ambitious systems from design through implementation and production.</li><li>
<strong>End-to-end engineering ownership:</strong>Proven ability to take complex projects from concept to delivery, make sound technical decisions, and drive execution without requiring fully defined requirements or established solutions.</li><li>
<strong>Comfort with ambiguity:</strong>A strong bias for action, a builder mindset, and the ability to work effectively in early-stage or rapidly evolving product environments where experimentation and rapid iteration are essential.</li><li>
<strong>Python proficiency:</strong>Strong programming skills in Python, with experience developing maintainable, efficient, and production-ready machine learning applications.</li><li>
<strong>Cloud engineering expertise:</strong>Hands-on experience building and deploying cloud-based services using AWS, Google Cloud Platform (GCP), or Microsoft Azure.</li><li>
<strong>Scalable data and inference systems:</strong>Experience working with high-volume data, streaming pipelines, real-time inference workloads, and diverse data storage technologies.</li><li>
<strong>Machine learning fundamentals:</strong>Strong understanding of statistical machine learning algorithms, transformer models, large language models, and their practical applications in production environments.</li><li>
<strong>Research and experimentation:</strong>Ability to evaluate emerging ML techniques, formulate testable hypotheses, design meaningful experiments, and translate research findings into reliable software solutions.</li><li>
<strong>Technical leadership:</strong>Demonstrated ability to raise engineering standards through architectural guidance, design reviews, mentorship, and the development of shared technical practices.</li><li>
<strong>Communication and collaboration:</strong>Excellent written and verbal communication skills, with the ability to explain complex technical concepts, align stakeholders, and collaborate effectively across multidisciplinary teams.</li><li>
<strong>Autonomy and adaptability:</strong>Ability to learn new technologies quickly, prioritize effectively, and deliver high-quality results in a fast-paced environment.</li><li>
<strong>AI agents and conversational systems (preferred):</strong>Experience building autonomous agents capable of handling multi-turn conversations while maintaining long-term context, consistency, and relevant customer information.</li><li>
<strong>Predictive modeling and user behavior (preferred):</strong>Strong background in modeling user behavior, designing experiments, and applying causal inference or counterfactual methods when full randomization is not possible.</li><li>
<strong>Distributed team experience (preferred):</strong>Previous experience collaborating with globally distributed engineering teams across different locations and time zones.</li><li>
<strong>Location and availability:</strong>Must be based in India, with eligibility to work in the applicable jurisdiction. Occasional travel may be required for team gatherings, project meetings, or customer engagements.</li><h2>Benefits</h2><li>
<strong>Remote-first working model:</strong>Work remotely from eligible locations in India, including Karnataka, Tamil Nadu, Telangana, Maharashtra, and New Delhi.</li><li>
<strong>Competitive compensation:</strong>Receive a competitive pay package aligned with your skills, experience, and location.</li><li>
<strong>Generous paid time off:</strong>Access time-off benefits designed to support personal commitments and work-life balance.</li><li>
<strong>Parental leave:</strong>Benefit from parental leave provisions to support employees and their families.</li><li>
<strong>Wellness leave:</strong>Access wellness leave to help maintain your physical and mental wellbeing.</li><li>
<strong>Healthcare benefits:</strong>Receive healthcare coverage and other benefits according to the applicable local employment package.</li><li>
<strong>Retirement savings:</strong>Access a retirement savings program, subject to local eligibility and plan terms.</li><li>
<strong>Technical ownership:</strong>Lead ambitious AI/ML projects and influence the design of intelligent customer engagement technologies.</li><li>
<strong>Continuous learning:</strong>Explore emerging AI frameworks, LLM technologies, machine learning techniques, and modern cloud infrastructure.</li><li>
<strong>Global collaboration:</strong>Work with talented professionals in a distributed, international environment that values diverse perspectives and shared learning.</li><li>
<strong>Career development:</strong>Strengthen your technical leadership, research, and production engineering expertise while contributing to high-impact products.</li><li>
<strong>Community engagement:</strong>Participate in supported volunteering and donation initiatives that encourage employees to create positive change in their communities.</li><li>
<strong>Collaborative culture:</strong>Join a team that values innovation, initiative, inclusion, experimentation, and continuous improvement.</li>