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.

Requirements

Required Skills & Qualifications

Nice to Have

Benefits