Machine Learning Engineering Manager

Vintti; Teletrabalho; BRL 160.000 - 200.000; Tempo integral

Resumo da oferta

A technology company is seeking a Machine Learning Engineering Manager to lead teams in designing and deploying large-scale ML and LLM systems. You will manage project lifecycles from experimentation to production, ensuring that AI initiatives have measurable business impacts. The ideal candidate has extensive experience in ML and NLP, strong leadership skills, and proficiency in relevant tech stacks. This remote role requires collaboration with cross-functional teams to drive innovations in AI.

Qualificações

• 5+ years of experience in Machine Learning, NLP, and Deep Learning.
• 2+ years leading teams delivering ML / LLM systems in production.
• Strong proficiency in Python and ML frameworks.

Responsabilidades

• Lead and mentor ML engineers and MLOps professionals.
• Manage end-to-end ML / LLM project lifecycle.
• Implement MLOps best practices.

Conhecimentos

Machine Learning

NLP

Deep Learning

Leadership

Communication

Cross-functional collaboration

Formação académica

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

Ferramentas

Python

PyTorch

TensorFlow

Hugging Face

MLflow

Kubeflow

Vertex AI

Descrição da oferta de emprego

Overview

Location: Remote - LATAM

Schedule: Full-time (8 hrs / day) — must have 4 hrs overlap with PST

About the Role

We’re looking for a hands-on Machine Learning Engineering Manager to lead cross-functional teams in designing, training, and deploying large-scale ML and LLM systems.

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, cloud budgets, and 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.