Senior ML/NLP Engineer

Job Title: Senior ML/NLP Engineer

Company Overview:
Noetiq Edge is a strategic consulting firm based in Canada that provides expertise and insights to firms across multiple industries including Finance, Supply Chain, Defence, Retail, Healthcare, and High-tech.

We establish trusted partnerships with organizations to ensure they have the strategy, information, technology, and talent required to succeed in a dynamic world.

Job Description:
We are currently seeking a Senior ML/NLP Engineer for an initial 1 year contract opportunity. As the successful candidate you will design and implement intelligent systems that interpret complex data for operational environments.

In this role, you will bridge the gap between research and production by developing scalable models that extract meaningful insights from unstructured information. You will work within a multidisciplinary team to deploy these solutions directly into the hands of users, ensuring that our automated systems are robust, efficient, and capable of performing in real-world scenarios.

This position is available 100% Remote in Canada.

Key Responsibilities:

• Design and implement machine learning pipelines that process large volumes of unstructured text and data to support decision-making processes.
• Develop and refine algorithms for information retrieval, entity extraction, and classification, ensuring high accuracy across diverse datasets.
• Optimize model performance and latency to ensure efficient execution on a variety of computing infrastructures, including resource-constrained environments.
• Create and manage end-to-end data workflows, including ingestion, cleaning, and annotation strategies to maintain high-quality training sets.
• Integrate machine learning outputs into existing software architectures and user interfaces to provide seamless experiences for end-users.
• Monitor deployed models for performance degradation or data drift and implement automated retraining or adjustment strategies as necessary.
• Collaborate with software engineers and product stakeholders to define technical requirements and ensure systems are secure and scalable.
• Analyze feedback from operational use to identify areas for model improvement and iterate on technical solutions rapidly.

Required skills:

• Proven experience as an ML/NLP Engineer building and deploying NLP/ML models in professional environments.
• Proficiency in modern programming languages used for data science, specifically Python, along with standard ML libraries and frameworks.
• Solid understanding of data engineering concepts, including experience building data pipelines and handling unstructured datasets.

Nice-to-have skills:

• Experience with Optical Character Recognition (OCR) or document processing technologies.
• Familiarity with edge computing principles or deploying software to non-cloud environments
• Knowledge of containerization and orchestration tools for managing model deployments.
• Background in industries involving physical operations, supply chain, or complex systems engineering.