Strong Middle Machine Learning Engineer Offline

The UKEESS Software House team is currently looking for a Strong Middle Machine Learning Engineer to join our team for a full-time position (remotely in Ukraine or in Lviv’s office).

About the Customer and the Project:
Our customer is the world’s largest DNA network from the USA. This presents a unique opportunity to work with more than 30 billion digitized global historical records, 100 million family trees, and 18+ million people in their growing database. Our customers help people discover their family stories and gain actionable insights about their health and wellness.

About the team:
You will be a part of the Data Science team, which produces the search index for all the website’s images (content). We use Computer Vision and NLP models to retrieve names, dates, and relationships from various sources, such as Censuses, Birth Certificates, and Newspaper Articles.
One of the teams delivers their models to our team as Python packages through a Model Repository. We create and operate data pipelines in AWS, using Terraform and Python to retrieve the images, run them through the models, and return the extracted data as JSON messages. Our typical projects process millions of images per day. We focus on throughput, cost, and error handling.
You will be responsible for learning our deployment pattern and taking ownership of creating and operating several of the new pipelines.

Responsibilities will include:

• Design, implement, and deploy ML models and algorithms throughout their lifecycle - from development to production
• Develop secure, high-performance microservices and data pipelines
• Develop and optimize scalable back-end services and APIs using Python
• Optimize models for efficiency, scalability, and real-time inference in production environments
• Collaborate with engineering, product, and business teams to understand requirements and deliver impactful ML solutions.
• Perform data analysis and preprocessing using frameworks such as PyTorch, TensorFlow, Keras
• Maintain and improve MLOps workflows, including model versioning, monitoring, and retraining.
• Stay up-to-date with the latest advancements in machine learning and AI technologies.

Requirements:

• 4+  years of experience building and deploying Python Applications
• 3+ years of Commercial experience with Machine Learning
• 3+ years of experience deploying production code to AWS (including EC2, SQS, SNS, S3, Lambda)
• Commercial experience with Terraform or CloudFormation
• Strong knowledge and commercial experience with SQL and NoSQL databases (preferred AuroraDB, DynamoDB)
• 1+ year of experience with customer-facing operations, including monitoring, cost analysis, and troubleshooting production issues
• Experience with CI/CD practices and tools (e.g., Jenkins, Git)
• English: Upper-intermediate at least (both spoken and written)

It will be a plus:

• Experience with frameworks such as PyTorch, or TensorFlow, or Keras
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes)
• Bachelor's degree in a related field or equivalent experience
   

What do we offer our new colleague?

• Competitive compensation (based on market data but also depending on the technical level of the candidate)
• Flexible work schedule
• 3 health packages to choose
• Annual paid vacation and state holiday celebration
• Free English classes (online)
• Individual approach to professional growth
• Lack of bureaucracy and micromanagement
• Modern, comfortable office facilities (a barbecue zone, kitchens, lounge rooms, coffee machines, etc.)
• Foreign business trips (after the war)
• On-site parking lot and charge station for Electric Cars
• Corporate gifts, celebrations, and fun activities
• Sports activities: ping-pong, soccer, work-out
   

Suppose you have a passion for solving challenging problems, building scalable, robust systems, love working with the latest technologies in a fast-paced, flexible environment, and are excited at the prospect of having a significant impact on products with more than 3 million paying subscribers. In that case, we want to talk to you! ;-)