Machine Learning Engineer

Position Overview

• Location Type: Remote
• Job Type: [Employment Type - Not specified]
• Salary: Not specified

We are seeking a Machine Learning Engineer to collaborate closely with the ML Architect on developing ML frameworks (TensorFlow, Scikit-Learn, PyTorch), an experimentation platform, and associated tools. This role involves building scalable, performant, efficient, and reliable large-scale distributed machine learning systems. You will work with cross-functional teams to deploy and integrate machine learning models, liaise with Business Units (BUs) to understand their ML needs and manage the cross-BU ML portfolio. Key responsibilities include optimizing feature extraction, transformation, and selection, managing Feature Stores for reusability, and ensuring the scalability, reliability, cost efficiency, and ease of use of the machine learning platform. You will also contribute to evaluating and adopting new technologies to enhance our machine learning capabilities.

Requirements

• Experience: 3-5 years of experience as an ML Engineer.
• Industry Preference: Preferably with a Gaming industry background.
• Frameworks: Experienced with ML frameworks (TensorFlow, Scikit-Learn, PyTorch).
• Model Lifecycle: Experienced with Model training, versioning, and monitoring.
• MLOps Practices: Strong background in MLOps practices, including CI/CD, containerization (Docker), orchestration frameworks (Kubernetes, Airflow), model serving tools (AWS SageMaker, Databricks MLFlow), model observability frameworks, automation, and feature stores.

Responsibilities

• Develop large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable.
• Collaborate with cross-functional teams to help deploy/integrate machine learning models.
• Liaise with the BUs for their ML needs and work on the cross-BU ML portfolio.
• Optimize feature extraction, transformation, and selection.
• Work with and manage Feature Stores for reusability across ML pipelines.
• Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform.
• Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities.

Benefits

• Health Insurance: Provided
• Flexible Working Hours: Offered
• Open Holidays: Provided
• Profit Distribution: For everyone
• Annual Trip & Social Activities: Provided
• Training & Conferences: Supported
• Child Care Vouchers: Offered
• Laptop & Peripherals: Choice provided
• Hotspot: Unlimited usage (PT)
• Office Locations: Porto, Aveiro, Coimbra (Physical option)
• Remote Options: Remote from Portugal, Remote from other countries (dependent on location and projects)
• Partnerships with Local Businesses: Provided
• Collaborative Culture: Politics-free environment, emphasis on teamwork, risk-taking, and communication.

About Mindera

At Mindera, we use technology to build products we are proud of, with people we love. Software Engineering Applications, including Web and Mobile, are at the core of what we do at Mindera. We partner with our clients to understand their products and deliver high-performance, resilient, and scalable software systems that create an impact on their users.