AI Summary
Lead cross-functional teams to build and deploy cutting-edge LLM and ML systems. Drive AI development from research to production, mentoring top engineers and collaborating with research and infrastructure leaders.
Key Highlights
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 deployment
Collaborate with Research, Product, and Infrastructure teams to define goals and success metrics
Technical Skills Required
Benefits & Perks
Fully remote work environment
Opportunity to work on cutting-edge AI projects
Job Description
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)
- 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