Machine Learning Engineer (Knowledge Systems)

About Us

Umaneo is a Canadian AI consulting firm composed of passionate, highly motivated experts on a mission to build custom AI solutions, with a fearless desire to disrupt the world for the best. The team takes a delightfully human approach to solve big business problems, delivered in elegantly designed solutions. What’s more, we attract some of the best talent and propose a human-centric, truly remote workplace, with an emphasis on developing our talented individuals to their true potential.

We work with clients who are global leaders in immersive entertainment, industrial automation, retail, and legal tech. Our crew has delivered over 30 AI projects spanning generative models, signal processing, time series, and computer vision. We work end-to-end, from project scoping and prototyping through deployment and monitoring, to deliver production-ready systems.

Position Overview

We are seeking a Machine Learning Engineer with strong experience building production AI systems, with a focus on natural language processing, information retrieval, and knowledge-based systems.

In this role, you will work across the full lifecycle of AI projects, contributing to system design, implementation, and deployment. You will collaborate closely with technical and business stakeholders to deliver robust, scalable solutions across a diverse set of applications.

You will also contribute to the design of systems that combine structured and unstructured data, including retrieval and reasoning pipelines.

Key Responsibilities

Design and implement machine learning systems, including:

* NLP and large language models (LLMs)

* Information retrieval systems (semantic search, hybrid search, ranking)

* Knowledge-based systems (knowledge graphs, structured reasoning)

Contribute to end-to-end ML workflows:

* Data preparation and pipeline design

* Feature engineering and model development

* Evaluation, iteration, and performance tuning

* Deployment and monitoring of production systems

Participate in system design and architecture decisions, including:

* Retrieval-Augmented Generation (RAG) pipelines

* Hybrid retrieval systems (vector + keyword + semantic)

* Integration of structured and unstructured data sources

Work closely with stakeholders to:

* Translate business problems into technical solutions

* Understand constraints and define appropriate approaches

* Iterate based on feedback and evolving requirements

Contribute to engineering quality and best practices:

* Write clean, maintainable, and well-documented code

* Participate in code reviews and technical discussions

* Ensure reproducibility and robustness of experiments

Stay current with advancements in AI, particularly in NLP and retrieval systems, and apply them pragmatically in real-world contexts

Qualifications

* Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field

* Demonstrated ownership of production systems

* Strong programming skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)

Hand-on experience with the following:

* Natural Language Processing (NLP), transformer models, and modern LLM ecosystems

* Information Retrieval and search systems (vector databases, hybrid search algorithms, ranking methods)

* Knowledge representation (e.g., knowledge graphs, ontologies)

* Designing and evaluating end-to-end AI pipelines

* Working with real-world, unstructured data (text-heavy systems in particular)

* Deploying ML systems in cloud environments (Azure, GCP, or AWS)

* Excellent communication skills, with the ability to explain complex concepts to technical and non-technical audiences

What We Offer

* The opportunity to work on cutting-edge AI projects in entertainment, industrial automation, and beyond.

* Flexible working arrangements (remote-first team).

* A collaborative environment where your growth and contributions directly shape project outcomes.

* Exposure to a variety of real-world AI challenges.