ML Architect (with Data Experience)

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

About the Role:

We are looking for an experienced ML Architect (with Data Experience) to design and improve AI/ML-driven solutions and data architectures. In this role, you will lead the discovery phase of projects, working closely with stakeholders to gather requirements, assess feasibility, and define high-level solutions.
Expected Involvement: +- 20 hrs/week.

Responsibilities:

• Review the architecture of an existing product & plan potential improvements

• Transform business features into technical requirements

• SOW estimation and planning

• Provide data-driven insights and visualizations of existing usage patterns

• Design and maintain the foundational architecture of the Product Ecosystem, ensuring scalability and performance

• Develop architectural blueprints and technical designs that adhere to best practices and industry standards

• Define and enforce coding standards, code reviews, and quality assurance processes

• Conduct architecture reviews to identify potential risks and mitigate technical debt

Essential knowledge, skills & experience:

• 5+ years of experience in data architecture, AI/ML solutions, or cloud-based data engineering

• Experience in data solution architecture and AI/ML integration in data platforms

• Proven experience in designing and implementing large-scale data engineering solutions in cloud environments (AWS, Azure, or GCP)

• Experience with Apache Spark, Databricks, or Azure solutions (or similar cloud-based data processing technologies)

• Experience with ML and Deep Learning frameworks (e.g., PyTorch, Hugging Face, TensorFlow)

• Experience with data warehousing, ETL processes, and real-time data streaming, with a focus on core data principles rather than specific database expertise

• Familiarity with open-source technologies and tools in data engineering

• Knowledge of architectural patterns and practices

• Understanding of different types of ML model usage

Nice-to-have:

• Relevant certifications (e.g.,AWS, GCP, or Azure)

• Familiarity with specific database technologies such as Snowflake, Redshift, DuckDB, MongoDB/Atlas, Hive, etc.

• Experience in discovery phases (gathering requirements, planning, and assessing feasibility)

• Knowledge of advanced analytics tools (Python) 

• Knowledge of Transformers architecture

Interview Steps:

1. GT interview with Recruiter

2. Technical interview

3. Final interview