Engineering Manager

Highbrow Technology Inc; México; Presencial; MXN 1.479.837 - 2.219.756; Jornada completa

Descripción de la vacante

A technology firm is seeking an Engineering Manager with expertise in Machine Learning and NLP. You will lead a team of engineers, oversee ML project lifecycles, and implement MLOps best practices. The ideal candidate has a deep understanding of machine learning architectures and strong leadership capabilities. This is a full-time contract position based in Mexico with potential for extension.

Formación

• 9+ years of strong background in Machine Learning, NLP, and modern deep learning architectures.
• Hands-on experience with ML frameworks like PyTorch, TensorFlow, Hugging Face, or DeepSpeed.
• 2+ years managing teams delivering ML/LLM models in production.

Responsabilidades

• Lead and mentor a cross-functional team of ML engineers and data scientists.
• Oversee the full lifecycle of ML projects from data collection to deployment.
• Collaborate with teams to define goals, milestones, and success metrics.

Conocimientos

Machine Learning

NLP

Deep Learning

Leadership

Communication

Collaboration

Educación

Bachelor’s or Master’s in Computer Science

Herramientas

PyTorch

TensorFlow

Hugging Face

DeepSpeed

AWS

GCP

Azure

MLflow

Kubeflow

Vertex AI

Descripción del empleo

Role

LLM – Engineering Manager (Python + Machine Learning)

Experience

9+ years overall; 2+ years leading ML/LLM teams

Engagement Type

Contract (2+ months) - Possible to extend for 6 months based on requirement

Start Date

Within 1 week

Availability

Full-time (8 hours/day) with at least 4 hours overlap with PST

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+ 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).