Machine Learning Engineering Manager (LLMs & Deep Learning)

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. Role Overview 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, 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. Commitments Required: 8 hours per day with an overlap of 4 hours with PST. Employment type: Contractor assignment (no medical/paid leave) Duration of contract: 3 months, possible extention Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico Two rounds of interviews (60 min technical + 30 min technical & cultural discussion) Roles & Responsibilities 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. Required Skills & Qualifications 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 (PhD preferred). Nice to Have Experience training or fine-tuning foundation models. Contributions to open-source ML or LLM frameworks. Understanding of Responsible AI, bias mitigation, and model interpretability. Work in a fully remote environment. Opportunity to work on cutting-edge AI projects with leading LLM companies.