Delivery Manager - DS​/ML - India

Delivery Manager Machine Learning

We are seeking a Delivery Manager (ML) with a strong background in Machine Learning, MLOps, and LLM engineering to lead and scale the execution of complex AI projects across multiple global teams. This individual will oversee the end-to-end delivery of high-impact ML and LLM initiatives from large-scale data preparation and model training to deployment and performance optimization.

The ideal candidate is a strategic operator and technical leader who can bridge research, engineering, and business delivery, ensuring excellence in execution, model quality, and stakeholder alignment. You will lead projects with 100+ team members, collaborate with AI researchers, ML engineers, and product leads, and drive innovation in tooling, automation, and process optimization.

• Lead and manage large, cross‑functional ML delivery teams (ML engineers, data scientists, MLOps, and annotators).
• Build scalable organizational structures and delivery mechanisms to support multiple concurrent ML / LLM programs.
• Define clear KPIs, quality goals, and success metrics for every project stage.
• Drive a culture of ownership, learning, and technical excellence through coaching, recognition, and gamified performance systems.

• Own end‑to‑end delivery of large‑scale ML projects from planning and training through deployment and monitoring.
• Translate research and product goals into executable delivery roadmaps.
• Identify and resolve risks, blockers, and dependencies proactively.
• Provide transparent reporting to senior leadership and research partners on delivery status, risks, and quality.

• Ensure delivery excellence in data pipelines, model development, and evaluation frameworks.
• Review ML architectures and promote best practices in reproducibility, experiment tracking, and model governance.
• Analyze performance data and error trends to improve training efficiency and output quality.
• Champion continuous improvement and innovation in ML delivery workflows.

• Partner closely with AI researchers, data infrastructure, and product teams to translate research insights into production‑grade ML systems.
• Collaborate with engineering leaders to streamline compute usage, tooling, and resource allocation.
• Contribute to design discussions around distributed training, fine‑tuning, and scalable ML infrastructure.
• Document and disseminate learnings to accelerate organizational ML maturity.

• 10+ years of experience in engineering, program management, or AI delivery, including 2+ years in ML / LLM project leadership.
• Proven ability to manage large‑scale delivery programs (100+ team members) across data, research, and engineering streams.
• Strong technical grounding in machine learning, NLP, and modern deep learning frameworks (PyTorch, Tensor Flow, Hugging Face, etc.).
• Working knowledge of MLOps pipelines (MLflow, Kubeflow, or Vertex AI) and cloud platforms (AWS, GCP, or Azure).
• Experience with data curation, training pipelines, and large‑scale annotation processes.
• Excellent communication, stakeholder management, and risk mitigation capabilities.
• Demonstrated success driving ML systems from research to production under tight timelines.

• Advanced degree in Computer Science, Machine Learning, or related field (PhD preferred).
• Hands‑on experience training or fine‑tuning foundation or LLM models.
• Experience managing compute‑heavy ML operations, including GPU scheduling and distributed model training.
• Understanding of Responsible AI, bias mitigation, and model interpretability.
• Background in gamification, performance motivation, or workforce engagement for large‑scale technical teams.

• Operate at the intersection of frontier AI research and large‑scale execution.
• Lead mission‑critical initiatives that accelerate AI innovation for global clients.
• Mentor and scale a world‑class ML delivery organization.
• Influence technical strategy, process design, and AI innovation in one of the fastest‑evolving spaces.

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