LLM - Engineering Manager

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. 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 will 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 should be comfortable coding, optimizing large‑scale training pipelines, and navigating the intersection of research, engineering, and product delivery.

Commitments :

8 hours per day with 4 hours overlapping PST.

Employment type :

Contractor assignment (no medical / paid leave).

Duration : 2 months.

Location :

Remote — candidates located in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, or Mexico may apply.

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

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 (Ph.D. 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

Fully remote environment

Opportunity to work on cutting‑edge AI projects with leading LLM companies

Seniority level Mid‑Senior level

Employment type Full‑time

Job function Other

Industries IT Services and IT Consulting

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