Machine Learning Engineer (Web and Mobile Business Unit)

Are you looking to join a team of professionals working with cutting-edge technologies and boost your career in Machine Learning?

We invite you to join our Data Center of Excellence, part of Sigma Software’s complex organizational structure that combines collaboration with diverse clients, challenging projects, and continuous opportunities to enhance your expertise in a collaborative and innovative environment.

Customer:

We operate across various business domains and work with some of the world’s top clients (those without NDAs can be found here: sigma.software/case-studies).

Our team highly supports employees’ freedom, independence in decision making, and the desire to deeply understand the client’s requests and identify the root of the problem. We believe that people who strive for this mindset are bound to succeed as recognized professionals and drivers of Big Data development in Ukraine.

Project:

Data Center of Excellence is a place where we collect the best engineering practices and unite them into one knowledge base to provide the best technical services to our clients.

We’re not just a team that comes together to write code. We are all willing to contribute to the field, either by participating in the life of the Data Center of Excellence or by constantly developing our own skills. In our unit, you can be the Data Engineer/Team Lead/Architect, or you can become a mentor, a person behind all the new technologies in the team, or an active listener, if you will. Whatever you decide, know that you’re not alone. Whether it’s a difficult task, an unordinary request from the client, or your next project choice, you’ll always have a mentor and teammates with the same mindset to come up with the best solution.

We hire people not for the specific project, but to join our team. It gives us a chance to get to know you better and ensures that we’ll provide the perfect match between the client’s needs and your professional interests.

If you’re ready to join the leading Data community, take this opportunity — let’s shape the future together!

Requirements:

• Advanced knowledge of Python and SQL
• Hands-on experience in model implementation and tuning using frameworks such as PyTorch, TensorFlow, or Keras
• Strong understanding of end-to-end machine learning development and deployment processes
• Proven experience with ML cloud platforms (e.g., AWS SageMaker, Vertex AI) and their ecosystem tools (e.g., SageMaker Pipelines)
• Experience in computer vision development
• Practical knowledge of MLOps principles and best practices
• Ability to design, build, and optimize ML pipelines for the end-to-end machine learning development cycle
• Experience of working with deep learning models for signal/speech processing and NLP
• Experience in scaling model training using multi-GPU infrastructure
• Familiarity with DevOps practices for AI/ML systems
• Track record of building and deploying production-grade AI solutions
• Proficiency in statistical analysis and data mining with the ability to apply these techniques effectively
• At least an Upper-Intermediate level of English

Responsibilities:

• Work in teams that handle a variety of tasks for clients and projects related to data and machine learning
• Collaborate closely with clients and their teams, maintaining clear and professional communication
• Take ownership of delivering key solution features
• Participate in requirements gathering and clarification, proposing optimal machine learning strategies, and leading ML implementation
• Represent the team as an ML technical expert in presale activities
• Design and develop core modules and functions, ensuring solutions are scalable and cost-effective
• Conduct code reviews and implement unit/integration tests to ensure quality
• Enhance distributed systems and infrastructure to improve scalability
• Support the client’s research team in implementing, training, testing, and fine-tuning deep learning models
• Work with researchers to identify best-fit models and evaluate open-source alternatives for language/signal processing, optimizing performance