Position: Machine Learning Engineer
Company: DesignKey
Experience required: 2y
English level: upper

We are looking for a Middle Machine Learning Engineer to join our Ukrainian team to work with a USA company and help with the integration of back-office enterprise systems into the existing architecture.

**REQUIREMENTS**:
·  	2+ years of experience in ML or similar
·  	Solid experience in building machine learning models both in batch and in real-time.
·  	Data Science and Machine Learning experience with Python, 
·  	Jupyter Notebooks, numpy/scipy, pandas, sci-kit-learn and Tensorflow/PyTorch
·  	In-depth knowledge of AI technologies, including natural language processing (NLP) and computer vision, using traditional techniques as well as deep learning
·  	Strong understanding of data engineering, database management, and cloud infrastructure.
·  	Experience with service development on AWS (Athena, S3, Lambda, Kinesis, Glue, SageMaker, Data Pipelines, Data Stores)
CI/CD experience
·  	Leading, and coaching our engineers on the team.
·  	Identify and fill team gaps and create the processes needed for teams to succeed.


**OTHER NECESSARY SKILLS** :
·  	English B2-C2
·  	 Ability to optimize algorithms for real-time or low-latency execution, considering hardware constraints
·  	Deep knowledge of model training, optimization, and investigating best options for a case
·  	Experience in deploying AI models in production environments is a plus
 
 
** PROJECT HIGHLIGHTS**:
·  	The application is in production
·  	The project utilizes development approaches such as code review, inherent quality, unit and integration testing, thorough automated end-to-end testing, continuous integration (CI), and releases as needed.
·  	Working in a distributed multinational team. The work schedule is from 10:00 AM to 7:00 PM EEST
·  	Staffing cooperation format
 
**RESPONSIBILITIES**:
·  	Engaging and maintaining professional communication with the customer's team
·  	Assuming responsibility for delivering significant solution components
·  	Participating in the process of gathering and clarifying requirements, suggesting optimal architectural approaches, and leading the implementation of data architecture
·  	Creating fundamental modules and functions, devising solutions that can grow and remain cost-efficient
·  	Conducting code assessments, crafting both unit and integration tests Expanding the distributed system and infrastructure to the next level of scalability
·  	Assisting the client's research team in implementing, training, testing, and refining deep learning models
·  	Constructing AWS machine learning infrastructure to uphold and manage model training and serving
·  	Formulating reusable project templates for establishing MLOps infrastructure, enabling continuous integration and deployment of machine learning models
·  	Cooperating with the research team to pinpoint optimal models and explore open-source alternatives in language and signal processing for achieving the most favorable outcomes.

**WHAT WE OFFER**:
- Small flexible team (1-10 people)
- Stable workplace
- Full remote
- 20 days of paid vacation
- 5 days of paid sick leave

**ABOUT THE PROJECT**:
USA leader in the solutions of beverage management for restaurants and bars.