Machine Learning Engineer

Key Skills

Amazon Elastic Compute Cloud-EC2, Amazon Simple Storage Service (S3), Apache Airflow, API, AWS, AWS Sagemaker, Data Analytics, Data science techniques, Deep Learning, Django, Docker, Facebook-Marketing, FastAPI, Machine learning techniques, MLflow, Python Programming

Job Description

• You'll help shape how data science is done at Fever. You'll be responsible for creating and maintaining an end to end machine learning pipeline.
• You'll work hand in hand with data scientists and data engineers helping on the experiment setup and model design.
• You'll bring to production models that will have a direct impact on the end user experience.
• You'll enforce best practices in data usage and model building.

On your first month in Fever:

• You will be fully integrated into the team. During this month you will have already participated in onboarding, you'll get a deep dive in the current data science efforts and you will have met the different departments at Fever.
• You'll get familiar with Fever's tech stack and frameworks.
• You will attend some of the Fever Original’s experiences like Candlelight

After 3 months in Fever:

• You’ll be able to come up with solutions to new difficult problems and you'll be generating impact and creating new business opportunities.
• You’ll have responsibilities and ownership over parts of our modeling pipeline or other critical tools.
• You will participate in some of the hackdays or hackathons we organise with other teams, and you will mostly know everybody from the data and engineering communities.

On your 6th month in Fever:

• You’ll have deployed to production models that have a direct impact on user experience.
• You'll be able to identify gaps in our platforms and processes and be a champion for continuous improvement
• You’ll be mentoring other new joiners to the team
• You will participate in some of the team buildings we organise for your team or the whole engineering team

Key responsibilities 

• Deploy trusted models that power Fever's decision making
• Design, build and support modern and scalable machine learning infrastructure, e.g.
• - Build a reproducible, organized, end to end machine learning pipeline.
• - Build model quality and usage monitoring systems.
• - Automate model training.
• Build tools to make our analysts and data scientists more efficient.
• Understand the technical trade offs of different solutions, implement them and make them scalable

About you

• You’re smart, get stuff done, have great energy, and thrive in a fast paced environment
• You have experience building reproducible, production-ready machine learning pipelines
• You have experience productionizing models
• You comply with defined coding standards, creating quality code
• You're an expert in Python3 and its data ecosystem 
• Experience with AWS (S3, EC2, …)
• You have experience in Docker
• You are proficient in business English

It would be a plus if you...

• You have worked Kubernetes, you've deployed services with EKS
• Have experience with SageMaker, MLFlow or similar frameworks.
• You have worked with Django, FastAPI or other python web frameworks.

It would be a plus if you...

• You have worked with Airflow or similar tools.
• You have worked in a multidisciplinary team working with roles such as data analysts, data scientists, marketing or product managers.
• You are familiar with tools and processes for reproducible, production-ready ML applications (e.g. data logging, ML workflows, model serving).
• You have worked with the API of the most popular marketing tools (Facebook, Google, Instagram, etc.)
• You have built data-powered tools either in a professional setting or as passion projects.

Benefits & Perks

• Attractive compensation package consisting of base salary and the potential to earn a significant bonus for top performance.
• Stock options.
• Opportunity to have a real impact in a high-growth global category leader
• 40% discount on all Fever events and experiences
• Home office friendly
• Responsibility from day one and professional and personal growth
• Great work environment with a young, international team of talented people to work with!
• Health insurance and other benefits such as Flexible remuneration with a 100% tax exemption through Cobee.
• English Lessons
• Gympass Membership
• Possibility to receive in advance part of your salary by Payflow.