Ai Technology Director

Bebeemachine; São Paulo; Presencial; BRL 100.000 - 140.000; Tempo integral

Resumo da oferta

A leading tech company in Brazil is seeking an experienced Machine Learning Engineering Manager to lead cross‑functional teams and drive the lifecycle of AI development from research to production deployment. The ideal candidate will have over 5 years of machine learning experience, particularly in NLP and deep learning, and will excel in leading teams and managing complex ML projects. This role offers a unique opportunity to impact AI initiatives and business outcomes significantly.

Qualificações

• 5+ years of experience in Machine Learning, NLP, and Deep Learning (Transformers, LLMs).
• 2+ years leading teams delivering ML/LLM systems in production.
• Strong proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face, DeepSpeed.

Responsabilidades

• Lead and mentor ML engineers, data scientists, and MLOps professionals.
• Manage end‑to‑end ML/LLM project lifecycle.
• Provide technical direction for distributed training and model optimization.

Conhecimentos

Machine Learning

Deep Learning

Leadership

Communication

NLP

Formação académica

Bachelor’s / Master’s in Computer Science, Engineering, or related field

Ferramentas

Python

PyTorch

TensorFlow

Hugging Face

MLflow

Kubeflow

Descrição da oferta de emprego

Job Description

We’re seeking an experienced Machine Learning Engineering Manager to lead cross‑functional teams in designing, training, and deploying large‑scale ML and LLM systems. As a hands‑on leader, you'll drive the full lifecycle of AI development— from research and experimentation to distributed training and production deployment—while mentoring top‑tier engineers and partnering closely with product, research, and infra leaders.

This role blends deep ML/MLOps expertise with strong leadership and execution, ensuring all AI initiatives translate into measurable business impact.

Key Responsibilities

• Lead and mentor ML engineers, data scientists, and MLOps professionals.


• Manage end‑to‑end ML/LLM project lifecycle: data pipelines, training, evaluation, deployment, and monitoring.


• Provide technical direction for distributed training, large‑scale model optimization, and system architecture.


• Collaborate with Research, Product, and Infrastructure teams to define objectives, milestones, and KPIs.


• Implement MLOps best practices: experiment tracking, CI/CD, model governance, observability.


• Manage compute resources, enforce Responsible AI + data security standards.


• Communicate technical progress, blockers, and results clearly to leadership and stakeholders.

Required Skills & Qualifications

• 5+ years of experience in Machine Learning, NLP, and Deep Learning (Transformers, LLMs).


• 2+ years leading teams delivering ML/LLM systems in production.


• Strong proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face, DeepSpeed.


• Experience with distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure).


• Knowledge of MLOps tools (MLflow, Kubeflow, Vertex AI, etc.).


• Excellent leadership, communication, and cross‑functional collaboration skills.


• Bachelor’s / 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/LLM frameworks.


• Knowledge of Responsible AI practices, bias mitigation, and model interpretability.