Are you looking for a team of professionals on top of cutting-edge technologies? Are you looking for a place to boost your Machine Learning career? We invite you to be a part of Sigma Software’s complex organizational structure that combines various clients, interesting projects, and activities to grow your professional skills.
Customer:
Our client is a community-powered fashion marketplace with over 30 million registered users across 150+ countries. It's a platform for discovering and celebrating personal style while promoting sustainable fashion by extending the life of millions of garments. Founded in 2011 and headquartered in London, with offices in Manchester and New York, our client employs around 400 people. In 2021, it became a wholly owned subsidiary of Etsy but continues to operate independently. The company is committed to diversity, inclusion, and fair recruitment processes, supporting visa sponsorship for certain roles and skill sets.
Responsibilities:
- Working and professionally communicating with the customer’s team
- Taking up responsibility for delivering major solution features
- Participating in requirements gathering & clarification process, proposing optimal architecture strategies, lead the data architecture implementation
- Developing core modules and functions, designing scalable and cost-effective solutions
- Performing code reviews, writing unit, and integration tests
- Scaling the distributed system and infrastructure to the next level
- Helping client’s research team with implementation, training, testing, and tuning of deep learning models
- Developing AWS machine learning infrastructure to support and maintain model serving and training
- Providing guidance and best practices to effectively and securely leverage Amazon SageMaker service for interaction with a model
- Creating reusable project templates to create the infrastructure for MLOps solutions for CI/CD of ML models
- Collaborating with a research team to identify best-fit models and open-source alternatives related to language and signal processing to obtain the best possible result
Requirements:
- Strong Python and SQL knowledge and experience
- Experience with PySpark and Airflow
- Experience with model implementation and tuning using popular Machine Learning frameworks like PyTorch, Keras, TensorFlow
- Ability to understand machine learning development and deployment processes
- Solid experience with SageMaker and all the features it provides (like Sagemaker Pipelines)
- Ability to create and adjust SageMaker pipelines for the end-to-end ML development cycle
- Experience in working with Deep learning models for processing
- At least an Upper-Intermediate level of English