Machine Learning Engineering Manager (LLMs & Deep Learning) at Gramian Consultancy

Job Title: Machine Learning Engineering Manager (LLMs & Deep Learning) at Gramian Consultancy

Date Posted: 2nd December, 2025.

Expiry Date: N/A

About the Job

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.

Your Job Description

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, building 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 & Employment Details

  • Work Schedule: 8 hours per day with an overlap of 4 hours with PST.
  • Employment Type: Contractor assignment (no medical or paid leave).
  • Contract Duration: 3 months, possible extension.
  • Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico.
  • Interview Process: Two rounds — 60-minute technical interview plus 30-minute 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 and budgets while ensuring compliance with data security and responsible AI standards.
  • Communicate progress, risks, and results to stakeholders and executives effectively.

The Job Requirements

Requirements

Required Skills & Qualifications

  • 9+ years 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+ years 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.

Benefits

  • Work in a fully remote environment.
  • Opportunity to work on cutting-edge AI projects with leading LLM companies.

Method of Application: Click on this link to get detailed information and apply

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