Senior Manager, Machine Learning

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager, Machine Learning based in India. This is a high-impact leadership role at the intersection of applied machine learning, conversational AI, and large-scale platform engineering. You will define and execute the ML strategy powering next-generation AI-driven communication systems used by hundreds of thousands of businesses globally. The role blends hands-on technical contribution with team leadership, requiring a strong “player-coach” mindset to guide architecture, model development, and production deployment. You will translate ambiguous product and business challenges into scalable ML solutions, shaping a roadmap that drives innovation in conversational intelligence and contextual AI systems. Working in a fast-moving, remote-first environment, you will collaborate across engineering, product, and research teams to bring cutting-edge AI capabilities into production. This is a role for leaders who thrive in complexity, enjoy building from 0-to-1, and are motivated by delivering real-world impact at global scale. Accountabilities: - Define and lead the machine learning roadmap, translating ambiguous business and product problems into clear, prioritized ML initiatives aligned with strategic goals. - Act as a “player-coach” by contributing hands-on to model development, system design, and experimentation while mentoring and guiding a team of ML engineers. - Build and scale production-grade ML systems focused on conversational AI, including LLM orchestration, embedding pipelines, and vector-based retrieval systems. - Establish robust ML/LLM Ops practices, including evaluation frameworks, monitoring systems, and performance metrics for non-deterministic AI systems at scale. - Drive the design and optimization of cloud-based ML infrastructure across AWS, GCP, or Azure, ensuring scalability, reliability, and cost efficiency. - Lead cross-functional collaboration with engineering, product, and business stakeholders to define KPIs, track outcomes, and ensure alignment on delivery timelines and priorities. - Recruit, mentor, and develop a high-performing ML engineering team, fostering a culture of experimentation, ownership, and operational excellence. Requirements: - 10+ years of experience in Applied Machine Learning or AI, including at least 3+ years in a leadership role managing ML engineers or data science teams. - Strong experience designing and deploying production-grade ML/AI systems at scale, including experience with LLMs, embeddings, vector databases, and conversational AI systems. - Proven ability to define and execute long-term ML strategy for complex, large-scale platforms or products. - Deep expertise in ML Ops / LLM Ops practices, including evaluation methodologies for generative and probabilistic models in production. - Strong software engineering and cloud background, with hands-on experience in AWS, GCP, or Azure and high-volume distributed systems. - Demonstrated ability to hire, scale, and lead high-performing technical teams in fast-paced environments. - Excellent communication and leadership skills, with the ability to influence stakeholders and drive alignment across multiple teams. - Preferred: Master’s or PhD in Computer Science, Machine Learning, or related field; publications or open-source contributions; experience in conversational AI and distributed global teams. Benefits: - Competitive compensation package aligned with senior leadership responsibilities - Fully remote-first working model with global collaboration opportunities - Generous paid time off, parental leave, and wellness support - Comprehensive healthcare coverage (region-dependent) - Retirement savings and financial wellbeing programs (where applicable) - Opportunity to lead cutting-edge conversational AI initiatives at massive scale - Strong culture of ownership, innovation, and continuous learning - Access to global engineering talent and cross-functional AI research collaboration. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. 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