Machine Learning Engineer
June 15, 2023
Airflow
AWS
Big Data
CI/CD
Cloud
Deep Learning
DevOps
Docker
ETL
GCP
Google Cloud Platform
Kafka
Keras
Kubernetes
Machine Learning
Python
PyTorch
Spark
Tensorflow
Description
• Would you like to be part of a Data Products and Machine Learning development startup? Join us! 🚀Mutt Data is a startup dedicated to building innovative systems using Big Data and Machine Learning technologies. • We use technologies like Spark, Airflow, Kubernetes, MLFlow, Kafka, Databricks, Astronomer, Kinesis, PostgreSQL, DBT, Airbyte, Amazon Web Services, and Google Cloud Platform, among many others. • We are looking for a Machine Learning Engineer that will help us productionize and deliver ML projects. If you are a person who likes building systems, proposing solutions, learning new tools, and designing architectures, we would love to get to know you! 🐶 • We operate with technology startups and large companies in Argentina, the United States, Brazil, Colombia, Spain, and Uruguay. We have an extremely technical team and we have extensive experience building and maintaining large-scale production data systems. • We are AWS and Astronomer Partners 👍 • We would like to keep going in this direction and we would love to have you join us. If you find that you like to learn new tools, teach your colleagues, reduce technical debt, contribute to complex solutions, listen and to be listened to, take control of technical problems, and work in a horizontal structure, this can be a good place for you. • These are some of the problems we solve 💪➤ Use reinforcement learning to optimize the advertising investment ➤ Build advertising auction systems in real-time ➤ Predict electricity consumption demand on a large scale ➤ Anomaly detection in activity levels of telecommunication services with millions of users. Implement stream processing systems to manage TBs of data ➤ Build flexible and scalable cloud architectures that optimize costs and allow services to grow exponentially ➤ Implement Deep Learning algorithms for video feeds data sources, to analyze and count people in customer care centers • Responsibilities 🧣➤ Lead the productivization of ML models following MLops best practices (orchestration, testing, monitoring, serving, etc) for our customers Aid data scientists develop useful ML POCs for either internal or client needs ➤ Manage the Machine Learning model's lifecycle and optimize such models when needed for better performance, latency, memory, and throughput ➤ Understand how to translate business and mathematical/statistical requirements to software implementations making wise trade-offs of time, quality, and client-specific needs ➤ Research new ML Engineering technologies (DS, DE, DevOps) and techniques that will enable us to improve our toolset, best practices, and derived business value ➤ Bridge the gap between DS and DE roles by handling foundational concepts of application development, infrastructure management, data engineering, and data governance ➤ Participate in defining the roadmap, timelines, and estimates for new projects ➤ Document and spread the internal knowledge of new best-industry practices in AI/ML ➤ Collaborate with Interview instances for Tech People (Exam Review and Technical Interview)
Requirements
• Proven work experience as a Machine Learning Engineer, ML Architect, Cloud Engineer, or similar roles. • In-depth understanding of AI/ML principles (neural nets, supervised and non-supervised ML models, time series forecasting, etc). • Knowledge of Modern Data Architectures including implementation of Data Warehouses and Data Lakes and Devops tool/stack and methodologies (CI/CD, Kubernetes, Docker, gitops, etc) • Past experience with data processing ETL and ML workflows (eg: Airflow, MLflow, DBT). • Understanding Deep Learning frameworks and technologies (eg: keras, PyTorch, Tensorflow). • Solid understanding of Python programming language and one other strongly typed language. • Knowledge of mathematical modeling and proficient statistical intuition. • Experience implementing Machine Learning based systems (ML model lifecycle, monitoring, etc.) and setting up MLOps pipelines from scratch • Capacity to develop implementation plans weighing pros and cons of different alternatives • Great capacity for teamwork • Solid command of the English language for writing technical documents such as Design Documents. • Great communication skills
Benefits
• Gympass: access to thousands of fitness + mindfulness + wellbeing studios and apps. • Additional Internet Connectivity stipend. • Welcome Kit - Mutt provides working equipment if needed (laptop, work chair, headset, external monitor, etc.) • Pedidos Ya Pay. • Up to 20% of the salary paid in USD (Tied to BCRA directives) • Mutt week! An additional week of vacation per year. • Paid AWS and GCP certification exams and materials. • Birthday free day! • In-company English lessons. • Social Paid Events • Worknmates Coworking spaces • Referral Bonuses. • Remote First Culture: flexible working time + flexible working location. • Annual Mutters' Day. • Annual Mutters' Trip.
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