Ingeniero de Aprendizaje Automático Senior para Sistemas Distribuidos

Placements24; Monterrey; Hybrid; MXN 2,233,000 - 3,350,000; Full time

Benefits offered by this job

Fully remote

Salary with performance bonuses

Professional growth opportunities

Job summary

Placements24 is seeking a Senior Machine Learning Engineer to design, build, and deploy ML models for large-scale distributed systems in a remote-first environment. You will tackle model training, inference at scale, and performance optimization.

The role requires strong Python proficiency, experience with TensorFlow or PyTorch, and hands-on MLOps. You will collaborate with researchers and software engineers on global R&D projects and mentor junior engineers.

Qualifications

• Master's or PhD in Computer Science, ML, or a related field.
• 5+ years of experience in machine learning engineering for distributed systems.
• Proficient in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms and containerization (Docker, Kubernetes).

Responsibilities

• Design, develop, and deploy ML models for large-scale distributed systems.
• Optimize ML algorithms for performance, scalability, and efficiency.
• Work with Spark, Ray, or Dask for training and inference.
• Build and maintain MLOps pipelines for CI/CD and monitoring.
• Collaborate with researchers and engineers to productionize models.
• Mentor junior engineers and share knowledge.

Skills

Distributed systems

Python

ML algorithms

Problem solving

Communication

Independent work

Education

Master's or PhD in CS/ML

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

Apache Spark

Ray

Dask

Job description

About the Role

Our client is a world-class Research and Development entity focused on Artificial Intelligence and Emerging Technologies. We are seeking a highly accomplished Ingeniero de Aprendizaje Automático Senior to join our fully remote team. This role is central to designing, building, and deploying sophisticated machine learning models within large-scale, distributed systems. You will tackle complex challenges related to model training, inference at scale, and optimizing performance across heterogeneous computing environments. The ideal candidate possesses a deep understanding of ML algorithms, distributed computing principles, and extensive experience in implementing and scaling ML solutions. This is a unique opportunity to work on challenging R&D projects with global impact, collaborate with leading experts in the field, and contribute to the advancement of AI, all within a flexible, remote-first work setting. If you are passionate about building robust and scalable ML systems, this role is for you.

Key Responsibilities

• Design, develop, and implement machine learning models for large-scale distributed systems.
• Optimize ML algorithms and workflows for performance, scalability, and efficiency.
• Work with distributed computing frameworks (e.g., Spark, Ray) for model training and inference.
• Develop and maintain robust MLOps pipelines for continuous integration, deployment, and monitoring.
• Collaborate with research scientists and software engineers to integrate ML models into production systems.
• Troubleshoot and resolve issues related to ML system performance and reliability.
• Stay current with the latest advancements in machine learning, distributed systems, and AI research.
• Mentor junior engineers and contribute to team knowledge sharing.

Requirements

• Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
• 5+ years of experience in machine learning engineering, with a focus on distributed systems.
• Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with distributed computing frameworks like Apache Spark, Ray, or Dask.
• Solid understanding of ML algorithms, model deployment strategies, and MLOps principles.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and collaboration skills, suitable for a remote team environment.
• Proven ability to work independently and manage complex projects.

Benefits

This is a fully remote position offering maximum flexibility and work-life balance. Our client offers a highly competitive salary, a comprehensive benefits package, and performance bonuses. We invest in our employees' professional growth through continuous learning opportunities, including access to cutting-edge research, training, and conferences. You will be part of an innovative and collaborative R&D team working on the forefront of AI.