Engineering Manager

Highbrow Technology Inc; A distancia; MXN 1,616,000 - 2,336,000; A tiempo parcial

Descripción de la vacante

A technology company is seeking an Engineering Manager with a strong background in Machine Learning and NLP to lead a cross-functional team. The candidate should have over 9 years of experience and at least 2 years in managerial roles. Responsibilities include overseeing ML projects' lifecycle, providing technical direction, and implementing best practices in MLOps. This is a full-time contract position based in Mexico, with potential for extension. Excellent leadership and collaboration skills are essential.

Formación

• 9+ years of strong background in Machine Learning, NLP, and deep learning architectures.
• Hands-on experience with ML frameworks and tools.
• 2+ years of managing teams delivering ML models in production environments.

Responsabilidades

• Lead and mentor a team of ML engineers and data scientists.
• Oversee the full lifecycle of ML projects.
• Provide technical direction on large-scale model training.

Conocimientos

Machine Learning

Natural Language Processing (NLP)

Leadership

Cross-functional Collaboration

Data Security Standards

Educación

Bachelor's or Master's in Computer Science

PhD preferred

Herramientas

PyTorch

TensorFlow

Hugging Face

MLflow

Kubeflow

Vertex AI

Descripción del empleo

Role: LLM – Engineering Manager (Python + Machine Learning) Experience: 9+ years overall; 2+ years leading ML / LLM teams Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico 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

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).