Machine Learning Engineering Manager
We are seeking a highly skilled and experienced Machine Learning Engineering Manager to lead our team in designing, training, and deploying large-scale ML and LLM systems. The ideal candidate will have a strong technical background, excellent leadership skills, and the ability to drive business results.
This role involves leading cross-functional teams, mentoring engineers, and collaborating with research, product, and infrastructure leaders. The successful candidate will be responsible for managing end-to-end ML/LLM project lifecycle, providing technical direction, implementing MLOps best practices, and ensuring responsible AI and data security standards.
* Lead and mentor ML engineers, data scientists, and MLOps professionals.
* Manage end-to-end ML/LLM project lifecycle: data pipelines, training, evaluation, deployment, and monitoring.
* Provide technical direction for distributed training, large-scale model optimization, and system architecture.
* Collaborate with Research, Product, and Infrastructure teams to define objectives, milestones, and KPIs.
* Implement MLOps best practices: experiment tracking, CI/CD, model governance, observability.
* Manage compute resources and enforce Responsible AI + data security standards.
* Communicate technical progress, blockers, and results clearly to leadership and stakeholders.
Requirements
The successful candidate will possess:
* 5+ years of experience in Machine Learning, NLP, and Deep Learning (Transformers, LLMs).
* 2+ years leading teams delivering ML/LLM systems in production.
* Strong proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face, DeepSpeed.
* Experience with distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure).
* Knowledge of MLOps tools (MLflow, Kubeflow, Vertex AI, etc.).
* Excellent leadership, communication, and cross-functional collaboration skills.
* Bachelor's/Master's in Computer Science, Engineering, or related field (PhD preferred).