AI Engineering Manager

Há 3 dias

Brasil Gramian Consulting Group Tempo inteiro

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 work 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 6+ hours with PST, specifically between 12pm - 6 pm PST.

Employment type: Contractor assignment (no medical/paid leave)

Duration of contract: 3 - 6 months, possible extension to other project and leadership roles

Location: LATAM, Europe

Two rounds of interviews (60 min technical + 30 min technical & cultural discussion)

NOTE: The role will be IC role, although experience as EM is needed. Managerial roles available upon completing this proejct.

Roles & Responsibilities

  • 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

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

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