Machine Learning Engineer

Description:

Querentia is seeking a Machine Learning Engineer to join its remote team in Canada. This role is central to designing, developing, and deploying GenAI and AI solutions within a cloud-based environment, especially utilizing Microsoft Azure and Databricks. The successful candidate will work closely with data engineers, architects, and business teams to build scalable and robust AI architectures and pipelines.

This position is ideal for candidates with strong proficiency in machine learning model development, data curation, deployment, and MLOps practices. A deep understanding of AI/GenAI plugin-based solutions, prompt engineering, and end-to-end model lifecycle is required.

Key Responsibilities:

• Develop and deploy GenAI/AI solutions including prompt engineering, analytical model development, testing, and integration (front-end and back-end).

• Design AI/GenAI architectures for plugin-based and custom business applications.

• Collaborate with data engineers to implement scalable data pipelines and structures for both structured and unstructured datasets.

• Cleanse, enrich, and validate datasets to enhance quality and consistency.

• Partner with data scientists to bring machine learning models into production cloud environments.

• Continuously monitor and optimize performance of AI models and pipelines.

• Automate deployment, scaling, and management of cloud data systems using scripting tools.

• Maintain detailed documentation of all architectures, workflows, and processes.

• Engage with stakeholders to clearly communicate model capabilities and AI solution benefits.

Preferred Skills and Qualifications:

• Strong hands-on programming experience in Python.

• Experience with Microsoft Azure, Databricks, and MLOps.

• Background in data ingestion, transformation, and machine learning lifecycle.

• Excellent communication skills to articulate technical solutions to business stakeholders.

• Ability to operate independently in a fast-paced, collaborative remote work environment.