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Lead MLOps Engineer in UKEESS Software House
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UKEESS Software House
UKEESS Software House is looking for Lead MLOpsfull-time day (either in the office in Lviv, or with the possibility of remote cooperation in Ukraine).
About the customer and the project:
This one of the world's largest family history and DNA resources. With the help of this service and DNA analysis, for example, it is possible to determine ethnic origin, susceptibility to allergies, various diseases, features of body structure, etc. (now there are about half a hundred definitions by DNA analysis). You can also build your family tree based on more than 30 billion digitized archival records (in the USA) from the 18th century. (+ this number is constantly growing) and learn interesting facts about your ancestors. In general, our customer is considered the largest in its space. :)About the team:
As part of the Data Science Engineering Team, you will be responsible for the deployment and operation of data science models designed for extracting data from images. This includes image classification and segmentation, handwriting recognition and natural language processing. The team accepts models from data scientists as Python programs using the SageMaker model registry. In addition, we create and maintain web applications for visualizing model results.
Responsibilities:
< span style="font-weight: 400; font-style: normal; text-decoration: none">Support of infrastructures and environments of all types, from development to production
Cooperation with specialists data scientists, data engineers, software engineers, and product teams to train, deploy, and manage ML models throughout their lifecycle from development to production
Deploying models in AWS EC2 autoscaling groups and
using AWS SQS, SNS, S3 and Lambdas to process all images via models
Developing MLOps pipelines using the Amazon SageMaker platform and its features
Working with project throughput, scaling, cost, and error handling
Developing ML-centric CI/CD pipelines
Using and writing Terraform libraries for infrastructure deployment
Diagnosis of complex problems involving several systems and technologies
Security Monitoring and Administration
Determining the possibilities of implementing innovative technologies
Experience and skills required:
3+ years of experience deploying and managing ML models
6+ years of commercial Python experience
3+ years of commercial experience with AWS (SQS, SNS, S3 and Lambdas)
Ability to design and implement cloud solutions and build MLOps pipelines on AWS
3+ years of commercial experience working with clients, including monitoring, cost analysis, and troubleshooting production issues
3+ years of experience as a team leader (including interview process and project management)
English: above average at least (spoken and written)
Preference will be:
Bachelor's degree in relevant field or equivalent experience
< /li>Experience with Terraform and Data Science
What do we offer a new colleague?
Competitive compensation (based on market data, but also depends on the technical level of the candidate)
Flexible work schedule
Annual paid leave
Free English lessons (online)
Health insurance or two alternatives to choose from
Individual plans for professional and personal development
Absence of bureaucracy and micro-management
Modern comfortable office (barbecue area, kitchen, lounge, etc.)
Foreign business trips (after the war)
Parking on the territory and a charging station for electric cars
Corporate gifts, holidays and entertainment
Спортивні активності
Надішліть нам своє резюме і давайте познайомимося! ;)
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The UKEESS Software House team is looking for a Lead MLOps Engineer to join our team for a full-time position (remotely in Ukraine or 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:
As part of the Data Science Engineering Team, you will be responsible for the deployment and operations of data science models designed to extract data from images. This includes image classification, image segmentation, handwriting recognition, and natural language processing. Our team accepts the models from data scientists as Python applications using the SageMaker Model Registry. Additionally, we build and maintain web applications for model output visualization.
Responsibilities will include:
Maintaining infrastructures and environments of all types, from dev to production
Work with Data Scientists, Data Engineers, Software Engineers, and Product teams to train, deploy, and manage ML models throughout their lifecycle - from development to production
Deploy the models on AWS EC2 autoscaling groups and
utilize AWS SQS, SNS, S3, and Lambdas to process all the images through the models
Developing MLOps pipelines leveraging the Amazon SageMaker platform and its features
Focus on and working with throughput, scale, cost, and error handling
Developing ML-oriented CI/CD pipelines
Using and writing Terraform libraries for infrastructure deployment
Diagnose complex problems involving multiple systems and technologies
Security monitoring and administration
Identify opportunities to adopt innovative technologies
Be an example of engineering excellence
Requirements:
3+ years of experience in deploying and managing ML models
6+ years of commercial experience with Python
3+ years of commercial experience with AWS (SQS, SNS, S3, and Lambdas)
Ability to design and implement cloud solutions and to build MLOps pipelines on AWS
3+ years of commercial experience with customer-facing operations, including monitoring, cost analysis, and troubleshooting production issues
3 + years experience as a team lead, including interviewing and project management
English: Upper-intermediate at least (both spoken and written)
It will be a plus:
Bachelor's degree in a related field or equivalent experience
Terraform and Data Science 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
If 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 which has more than 3 million paying subscribers, then we want to talk to you! ;-)
