Opportunity to accelerate the pace of digitalization & ecommerce growth through advanced technology, business intelligence and analytics.
Driving high-impact insights enhancing decision making across the entire organization.
Driving brand equity and digital sales through enhanced digital experiences
Interaction with senior business and ecommerce leaders on regular basis to drive their business towards impactful change
Become part of a fast growing international and diverse team
We are Metyis. We are a dynamic and forward-thinking consultancy firm that operates across a wide range of industries, creating solutions that are tailored to specific needs. We bring long-lasting impact and growth to our partners and clients.
With our multidisciplinary teams we create bold strategies and innovative solutions that are tailored to our client’s needs and help them capitalizing opportunities. Together we strive to bring long-lasting impact and celebrate collective victories.
At Metyis we share and entrepreneurial mind-set, a compelling passion to create and, more importantly, a firm belief in our partnership-driven business model. This is embedded in our culture and safeguarded as we evolve. Our team counts over 450 ambitious professionals with various backgrounds, spread over several continents. Our work environment unifies creative problem-solving and strategic thinking. We provide resources to visionaries who understand the direction that the world is moving. Tomorrow’s world is data-driven. It is digital. It is international.
Become part of the journey, become part of Metyis. Partners for impact.
As a Machine Learning Engineer, you will combine Software Engineering with Machine Learning techniques to build efficient, scalable and reliable data-driven systems to predict events and automate processes. You will also build pipelines for deploying models faster and for monitoring its quality and robustness.
Work alongside experienced engineers, data scientists and product owners to identify business opportunities, design and create new machine learning applications, all the way to deploying them to production
Improve scalability, speed and performance of existing models
Contribute to the full life cycle of ML models – data analysis, modeling, tuning & productization
Apply Software Engineering practices to Machine Learning Development in order to deploy scalable applications.
Build feature stores to structure and manage model features ready to be used for model training.
Partner with Data Engineers to create data cleansing and transformation processes to support model training and evaluation.
Partner with Data Scientists to understand model performance and robustness and the best algorithms to be applied.
Partner with Data Visualization Specialists and Scientists to create online and offline evaluation metrics and dashboards to monitor model and feature drift.
Proven experience in machine learning applications and how to deploy them in a scalable and efficient manner.
Proven experience in one or more object-oriented languages, including Scala, Python, Java or C++.
Proven experience working with Apache Spark, Tensorflow, Caffe, Torch, Theano, or Scikit-Learn.
Proven experience in full cycle machine learning libraries and platforms (i.e. PyCaret, Keras, AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform)
Proven experience in MLOps projects and implementations
Proven experience in deep learning in one or more domains of application (I.e. Image, Video or sound)