Machine Learning Engineer

Mutt Data is a startup dedicated to building innovative solutions based on Machine Learning and Big Data technologies. We love to work with the best tools: building data pipelines with Airflow, Spark, dbt; online inference and training with Vowpal Wabbit; powering reliable MLOps implementations with MLFlow, Sagemaker and using Kubernetes to manage resources, among others. We also have a long and prosperous relationship building modern data architectures in AWS and a growing one with GCP.  
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 algorithms, designing ML strategies or tackling hard mathematical/statistical problems, we would love to get to know you! 
We operate with technology startups and large companies of Argentina, the United States, Brazil, Colombia, Spain and Uruguay. We have an extremely technical team and we have extensive experience in ML + Data Engineering projects. We would like to keep growing in this direction with you. If 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 investmentBuild advertising auction systems in real timePredict electricity consumption demand on a large scaleAnomaly detection in activity levels of telecommunication services with millions of users. Implement stream processing systems to manage TBs of dataBuild flexible and scalable cloud architectures that optimize costs and allow services to grow exponentiallyImplement 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 developing useful ML POCs for either internal or client  needs.Manage Machine Learning models 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  Essential 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 scratchCapacity to develop implementation plans weighting pros and cons of different alternativesGreat capacity for teamworkSolid command of the English language for writing technical documents such as Design Documents.Great communication skills
What will set you apart for this role:Experience working with the Modern Data Stack.Hands-on experience working with cloud-based AI services (AWS Sagemaker, AWS Textract, GCP Vertex AI, or similar etc).Deep knowledge of software development methodologies.Positive problem-solving attitudeExperience working in client facing tech consultancy roles.A proven track record of delivering high quality solutions.Certification in cloud platforms (such as AWS Machine Learning)Experience with Python Data libraries (such as SQLAlchemy, Alembic, Great Expectations, etc) 
Benefits: BDay Free day! In-company English lessons Referral bonuses Remote First Culture : Flexible Working Time + Flexible Working LocationAnnual Mutters’ Day Annual Mutters’ Trip Fun activities!