Machine Learning Engineer - Remote within Spain
Barcelona, Catalonia, Spain
Mad Collective
At Mad Collective we are proud of our diversity (over 32 nationalities) and believe it is one of the most important contributors to our success. We’re 180+ people energized about our future and enjoying everything a high-growth company has to offer.
We offer a hybrid-remote work schedule which enables you to find the right combination of work from home and in-office collaborative time with your team.
Join the collective and go mad with us!
What you will do:
You will be part of the Data team working closely with technology teams solving challenges that touch all parts of the business (Marketing, Finance, Product, Billing, and Development). You will be responsible for the entire Machine Learning lifecycle from building data pipelines, to prototyping models, all the way to deploying models to production.
Main tasks
- Develop, test and implement predictive algorithms by using state-of-the-art Machine Learning solutions, and statistical models
- Automate data pipelines that serve models in the cloud (AWS)
- Develop and maintain pipelines for current and new models using AirFlow.
- Work with development teams to allow for easy deployment of models
- Improve scalability, speed and performance of existing models
- Collaborate with cross-functional teams such as product, development, operations, marketing amongst others; identify use cases for machine learning applications
- Extract, clean, combine and model data from multiple sources
- Partner with data scientists, analysts or engineers on data modeling, data processing and analysis
- Find creative solutions to problems related to customer lifetime value, ranking, recommendation, and pricing
Requirements
- Minimum 2 years of Software Development experience and at least 1 year in a Machine Learning Engineer/Data Scientist role
- Working experience of developing Machine Learning models in production environments
- Experience building backend applications and REST APIs
- Strong quantitative skills (Statistics, Probability, Machine Learning)
- Ability to design software systems complying with software engineering best practices for the full software development life cycle (MLOps lifecycle)
- Experience with the following tools / services:
- Advance coding skills in Python (numpy, pandas, scikit-learn, .. )
- AWS services (S3, DynamoDB, Redshift, EC2, Sagemaker, )
- Docker and Docker ecosystem
- Git, CI/CD tools and Unit/integration testing
- Business Level English: all spoken and written business communications are in English
It will be super nice if you also have:
- Ability to write advanced queries in SQL and working knowledge of databases
- (MySQL, Redshift, MongoDB, etc...)
- Hands-on analytical experience on large volumes of data (Spark, etc.).
- Experience in building large scale, distributed systems
- AWS Fargate o Kubernetes, Terraform, MLFLow
Benefits
- Private Health and Dental Insurance plan for employees.
- Subsidized gym memberships and fitness classes.
- Monthly internet allowance.
- Working from home setup allowance.
- Company sponsored Spanish, Catalan and English classes.
- Sponsored training and development.
- Quarterly company bonus programme.
- Top notch Apple equipment.
- Remote policy and flexible working hours
- Flexible Bank Holidays. Design your own working calendar with a lengthy consecutive vacation day policy.
- Day off for your birthday.
- Hybrid remote model office
*Please note: All applications must be submitted in English
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs AWS CI/CD Data pipelines Distributed Systems Docker DynamoDB EC2 Engineering Finance Git Kubernetes Machine Learning MLFlow ML models MLOps MongoDB MySQL NumPy Pandas Pipelines Prototyping Python Redshift SageMaker Scikit-learn SDLC Spark SQL Statistics Terraform Testing
Perks/benefits: Career development Flex hours Flex vacation Health care Home office stipend Salary bonus Startup environment
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