Position: Machine Learning Architect
Company: Dresslab
Category: Lead
Experience required: 5y
English level: upper

Machine Learning Architect
Dresslab UA is a subsidiary of the German company Dresslab GmbH which provides advanced developments in digitalizing clothes and people, using the latest artificial intelligence approaches. Dresslab is a leading technology partner in the textile and fashion industry. The company's goal is to evolve in the fashion industry - from digitizing clothes in production to a client who uses his model in a virtual fitting room. We provide a user experience in which online shopping - Internet resources, and the user - offline, which takes the client to a new level of experience. We are currently working on the 3D Virtual Fitting Room, a digital version of the standard stand-alone fitting room. It allows customers to try on clothes, decide on the size, look at themselves, and it's all online. The platform helps you get a complete immersion for the best experience.
 
YOU ARE
A Machine Learning Architect interested in building and delivering AI/ML-powered solutions. You will help us design and implement ML and data pipelines, solution infrastructure, and lead product teams.
You should be strongly competent in Machine Learning/Deep Learning models and model lifecycle, have a solid knowledge of DevOps/MLOps principles and solution architecture and understand the ML product team’s collaboration model.
 
A candidate should demonstrate such experience and abilities as
MS degree in computer science or related field
5+ years of relevant background including 2+ years of design and implementation of enterprise-scale AI/ML solutions in AWS, GCP, or Azure clouds
Designing sustainable architectures, performing trade-off analysis of different architecture tactics and patterns, and applying proven architecture design approaches and methodologies
Customer-facing experience of discovery, assessment, execution, and operations
Hands-on expertise in ML operationalization
Driving projects roll-outs from requirements gathering to go-live
Kubernetes platform and its design patterns
Strong requirements gathering and estimation
Upper-Intermediate English level or higher
 
Your extra power reveals in the following experience
Relevant Cloud Architecture certification from any of the three major cloud platforms (AWS/Azure/GCP)
Pre-sales or enterprise consulting
Building solutions with Kubeflow, MLflow, or similar
Hadoop ecosystem and Databricks
Workflow orchestration platforms like Airflow
Designing and building feature stores
Message queues and streaming platforms
YOU WANT TO WORK WITH
Bringing your deep expertise in cloud architecture/DevOps to analyze and recommend enterprise-grade solutions for operationalizing AI/ML Analytics
Developing end-to-end (Data/Dev/ML) Ops pipelines based on an in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably
Prototyping and demonstrating solutions for clients in customer environments
Using your judgment to craft solutions to complex problems or seeking guidance as needed
Developing assets, accelerators, and thought capital for your practice
Staying current on new products that clients could use
Communicating use cases, requirements, and expectations with stakeholders
Guiding Engineering and Data Science teams on ML systems production lifecycle
Guiding Data Science teams on model operationalization strategies
Educating Product teams on best practices for putting ML systems in production
TOGETHER WE WILL
Operationalize our clients’ AI solutions by leveraging best practices in DevOps, Machine Learning, and Solution Architecture
Maintain synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
Participate in international events
Have the possibility to work with the latest modern tools and technologies on different projects
 
ADVANTAGES FOR CANDIDATE: 
The availability of specialized equipment for work;
Stable and competitive salary; 
 Flexible working schedule;
Convenient office in Vinnytsia;
Monthly team activities;
Medical insurance;
Benefits - Gym, Swimming pool, Hobby circles; 
Certification training;
Learning English and German;
Review of working conditions every 6 months in case of improving skills and gaining new skills;
Participation in large-scale industry conferences.