Remote Machine Learning Engineer

Summary

Join Our Data Products and Machine Learning Development Startup! Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies. We are looking for a Machine Learning Engineer who can help us take our team and expertise to the next level.

Requirements

• Proven Expertise: Demonstrated work experience in roles such as Machine Learning Engineer, ML Architect, Cloud Engineer, or similar
• AI/ML Proficiency: In-depth understanding of AI/ML principles, encompassing neural networks, supervised and unsupervised ML models, time series forecasting, and more
• Data Architecture Knowledge: Familiarity with Modern Data Architectures, including the implementation of Data Warehouses and Data Lakes, as well as DevOps tool/stack and methodologies (CI/CD, Kubernetes, Docker, gitops, etc.)
• ETL and ML Workflow Experience: Previous involvement with data processing ETL and ML workflows, e.g., Airflow, MLflow, DBT
• Deep Learning Competence: Understanding of Deep Learning frameworks and technologies such as Keras, PyTorch, Tensorflow
• Programming Skills: Strong grasp of Python programming language and proficiency in at least one other strongly typed language
• Mathematical and Statistical Acumen: Knowledge of mathematical modeling and proficient statistical intuition
• MLOps Mastery: Experience in implementing Machine Learning-based systems, including ML model lifecycle management, monitoring, and setting up MLOps pipelines from scratch
• Strategic Thinking: Ability to develop implementation plans by weighing the pros and cons of different alternatives
• Exceptional capacity for teamwork
• English Intermediate Level
• Spanish Advanced Level

Responsibilities

• Lead ML Model Productization: Champion the productization of ML models following MLops best practices, including orchestration, testing, monitoring, and serving, to benefit our clients
• ML POC Development: Collaborate with data scientists to develop meaningful ML Proof of Concepts (POCs) for internal and client requirements
• ML Model Lifecycle Management: Oversee the lifecycle of Machine Learning models, optimizing them when necessary to enhance performance, latency, memory, and throughput
• Business-Technical Translation: Translate business and mathematical/statistical requirements into software implementations, making informed trade-offs between time, quality, and client-specific needs
• Research and Innovation: Explore emerging ML Engineering technologies (Data Science, Data Engineering, DevOps) and techniques to enhance our toolset, best practices, and overall business value
• Bridge DS and DE Roles: Act as a bridge between Data Scientist (DS) and Data Engineer (DE) roles by handling foundational concepts of application development, infrastructure management, data engineering, and data governance
• Project Strategy: Participate in defining project roadmaps, timelines, and estimates for new initiatives
• Knowledge Sharing: Document and disseminate industry-leading practices in AI/ML within the organization
• Technical Interviews: Collaborate on interview processes for technical personnel, including exam reviews and technical interviews

Benefits

• Gympass or Sport Club
• Additional Internet Connectivity Stipend
• Welcome Kit: Mutt provides necessary working equipment if needed, such as a laptop, ergonomic chair, headset, external monitor, and more
• Pedidos Ya Pay
• Social Paid Events
• Offi Coworking Spaces
• Salary in USD (Up to 20%)
• Mutt Week: Get an additional week of vacation each year
• Paid AWS and GCP Certification Exams
• Birthday Free Day
• In-Company English Lessons
• Referral Bonuses
• Remote First Culture
• Annual Mutters' Trip