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UKEESS Software House
About the command: span>
after receiving new knowledge and skills , you will be involved in studying our deployment model. Style = "font-weight: 400; font-style: normal; text-disocoration: none"> span> responsibilities: span>
after acquiring the required knowledge of ML: span>
Support and Improvement of MLOPS Working Processes, including models, monitoring and retraining. span>
Design, Introduction and Deployment of ML models and algorithms throughout their life cycle-from development to production span>
Optimization of models for efficiency, scalability and output in real-time in the production environment span>
To be aware of the latest achievements in the field of machine learning and artificial intelligence technologies
Required Experience and Skills:
4+ years of commercial experience with Python span>
3+ years of commercial experience in working with AWS span>
Commercial experience in Terraform or Cloudformation
Knowledge and Commercial Experience with SQL and NOSQL Databases
Experience with CI/CD (for example, Jenkins, Git)
English: above average (spoken and written) span>
The advantage will be:
Practical experience in working with Machine Learning
Experience in Customer Operations, including Monitoring, Cost Analysis and Probleming Problems span>
Experience with Frameworms such as Pytorch, Tsensorflow or Keras
Knowledge of Containerization and Orchestration Tools (eg Docker, Kubernetes) span>
Bachelor's Degree in the relevant industry or equivalent experience span>
What do we offer a new colleague? FONT-STYLE: Normal; Text-Decoration: None "> Compensation (based on market data, but also depends on the technical level of the candidate) span> Flexible Work schedule span> Annual paid vacation span> Free English Lessons (Online) span> Health Insurance or two alternatives to choose Individual Plans for Professional and Personal Development Lack of bureaucracy and micro management Modern comfortable office (barbecue area, kitchen, recreation rooms, etc.) Out-of-Business (after war) Parking on the territory and charging station for electric vehicles span> Corporate Gifts, Holidays and Entertainment span> Sports Activities: Table Tennis, Football, Vorkaut span>
Send to us your resume and let's get acquainted!;) span>
------------------------------------------------------------------------------------------------------------------------------------------ FONT-STYLE: Normal; Text-Decoration: None "> The Ukess Software House Team Is Looking for A SPAN>
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 Bilion Digitized Global Records, 18+ Million People in Their Growing Database. FONT-STYLE: Normal; Text-Decoration: None "> about the team:
You Will Be A Part of the Data Science Team, WHICH PRODUCES OF 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.
After gaining new knowledge, you will be responsible for learning our deployment pattern and taking ownership of creating and operating several new pipelines.
Responsibilities will include:
Develop and optimize scalable back-end services and APIs using Python
Develop secure, high-performance microservices and data pipelines
Collaborate with engineering, product, and business teams to understand requirements and deliver impactful ML solutions
After gaining mandatory knowledge:
Perform data analysis and preprocessing using frameworks such as PyTorch, TensorFlow, Keras
Maintain and improve MLOps workflows, including model versioning, monitoring, and retraining
Design, implement, and deploy ML models and algorithms throughout their lifecycle — from development to production
Optimize models for efficiency, scalability, and real-time inference in production environments
Stay up-to-date with the latest advancements in machine learning and AI technologies.
Requirements:
4+ years of commercial experience with Python development
3+ years of commercial experience with AWS
Commercial experience with Terraform or CloudFormation
Strong knowledge and commercial experience with SQL and NoSQL databases
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:
Knowledge or experience with ML
Experience with customer-facing operations, including monitoring, cost analysis, and troubleshooting production issues
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! ;-)