Position: Senior ML Engineer
Company: WorkNest Technologies
Experience required: 5y
Category: Python
English level: upper
Published: 2022-04-01T00:00:00+03:00

We are looking for passionate, ambitious, and excellent software engineers that want to break boundaries, move mountains and shape the future of AI

Our platform enables business users to build and run AI applications safely, quickly, and efficiently - all codeless, self-serviced. 
We are looking for passionate, ambitious, and excellent software engineers that want to break boundaries, move mountains, and shape the future of AI.
Wayto AI engineers are Kubernetes experts, develop cutting-edge technologies and strive to get the best user experience and efficiency for our customers.

In this role, you will take the main part in defining and developing the Wayto AI platform.

**Requirements:**
•	Strong Python background, specifical proficiency with ML libraries (Scikit-Learn, Pandas, Pytorch, TF, etc.)
•	B.Sc in Mathematics/Statistics/Physics/Computer Science or a related field
•	Practical experience with tabular data and time series.
•	Experience in Microservices architecture, cloud technologies, Docker/K8s
•	Ability to design and own a feature through all its phases
•	3+ years as a Machine learning Engineer – **advantage**   
•	M.Sc. in computer science, electrical engineering, physics, or related areas from a top university. PhDs – **strong advantage**.
•	Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production – **advantage**
•	Experience with data pipelines / big data compute – **advantage**
•	Fluent English

**What you’ll be doing:**
•	Work closely with the software development and research teams to create efficient training schemes for deep-learning-based algorithms 
•	Apply your scientific knowledge to analyze and collect data, identify problems, devise solutions and construct methodologies. 
•	Develop machine learning and deep learning models for time series and tabular data.
•	Learn and Implement cutting-edge ML algorithms. 
•	Create and automate data pipelines including data extraction, validation & anomaly detection, indexing, and other data-related tasks 
•	Follow your project from ideation to implementation 
•	Contribute to a wide variety of projects using a range of technologies and tools