Delivery Manager – DS/ML

November 3

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Turing

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Artificial Intelligence • SaaS • Enterprise

Turing is a leading company in the field of artificial intelligence, specializing in the advancement of AGI (Artificial General Intelligence) and the evaluation and training of large language models (LLMs). Turing offers a comprehensive range of AI solutions, including model performance assessments, multimodal capabilities integration, and custom engineering for enterprises looking to optimize their AI operations. The company bridges cutting-edge AI research with practical applications, empowering organizations to leverage advanced AI for various real-world challenges.

1001 - 5000 employees

Founded 2018

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

📋 Description

• 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

🎯 Requirements

• 10+ years of experience in engineering, program management, or AI delivery • 2+ years in ML/LLM project leadership • Proven ability to manage large-scale delivery programs (100+ team members) • Strong technical grounding in machine learning, NLP, and modern deep learning frameworks (PyTorch, TensorFlow, 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.

🏖️ Benefits

• Amazing work culture (Super collaborative & supportive work environment; 5 days a week) • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience) • Competitive compensation • Flexible working hours