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We are seeking a hands-on Machine Learning Engineering Manager to lead cross-functional teams building and deploying cutting-edge LLM and ML systems. In this role, you’ll drive the full lifecycle of AI development — from research and large-scale model training to production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You’ll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that all AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines, and navigating the intersection of research, engineering, and product delivery.
Job Responsibility:
Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals
Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment
Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics
Provide technical direction on large-scale model training, fine-tuning, and distributed systems design
Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML
Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards
Communicate progress, risks, and results to stakeholders and executives effectively
Requirements:
9+ yrs of strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs)
Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed
2+ yrs of proven experience managing teams delivering ML/LLM models in production environments
Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure)
Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines
Excellent leadership, communication, and cross-functional collaboration skills
Bachelor’s or Master’s in Computer Science, Engineering, or related field
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