Job Description

Machine Learning Engineer

Company Overview

Founded in 2016 and commercially launched in 2018, chata.ai is a Canadian-based technology company that has developed an AI-driven business intelligence platform that empowers users to make data-driven decisions more easily, more intuitively, and more often. The foundation of chata.ai's platform is advanced Natural Language Understanding (NLU) technology that allows individuals to gain insights from their data by asking a simple question.

We are applying Software Engineering, Natural Language Processing (NLP) and Machine Learning (ML) to solve some of the world's toughest data access problems. We have high expectations of communication, accountability, and curiosity, and are looking for those who would be inspired and stimulated in such an environment.

Position Summary

We are seeking a creative and disciplined Machine Learning Engineer to shape the future of our ML capabilities. Your primary focus will be researching, prototyping, and deploying production-ready solutions to complex problems in the NLP domain. You'll collaborate with engineers, architects, and data scientists to design, build, and deploy scalable systems that power our ML capabilities.

You'll spend most of your time solving challenging technical problems and building high-quality code that supports NLP models and highly scalable backend services. We prioritize deep work and technical excellence. You'll have the autonomy to focus on what you do best with minimal administrative interference in an environment that encourages rapid innovation.

Responsibilities

Research and apply emerging software engineering methods, techniques and technologies. Drive continuous improvement of our software product. Build on and adapt existing methods in software engineering for our problem domains. Collaborate with data scientists to assist the development of new Machine Learning models. Develop the high-quality, scalable, robust and performant code needed to support Machine Learning model data generation, training, inference, and deployment to Production. Investigate data augmentation techniques to enable high accuracy Machine Learning model training. Research, develop and use graph representations, knowledge bases, and graph embeddings to condition machine learning models on, and augment data. Participate in the entire application lifecycle, including code reviews, implementation and troubleshooting.

Minimum Requirements

Bachelor's or Master's Degree in Computer Science, Software Engineering, Computer & Electrical Engineering, Math, Physics, Statistics, or related discipline. 3+ years of professional backend software development experience. Expert-level proficiency in Python, OOP, and functional programming. Proponent of test-driven development and advocate for clean, maintainable code. Strong foundation in CS fundamentals, algorithms, data structures, and computational complexity theory. Proficiency in relational databases, especially SQL, and working with large data sets. Professional experience operationalizing Machine Learning models for scalable Production environments. Professional experience with the standard ML and data packages such as PyTorch, Tensorflow, Scikit-learn, Pandas, spaCy, Hugging Face and NLTK. Exposure to various vector embedding databases such as Faiss, PgVector, Milvus or ElasticSearch. Proven expertise in acceleration techniques such as multi-threading, multi-processing and distributed computing. Solid background in REST API design, data pipelines and implementation, Python web frameworks such as Flask or FastAPI. Hands-on experience with Docker, Kubernetes and, microservices architecture. Competency in cloud computing development and platforms such as Google Cloud Platform, Azure and/or AWS. Experience with Agile development best practices. Proficient understanding of code versioning tools such as Git. Intellectual curiosity, self-motivation, creativity, critical thinking, and innate problem-solving skills with a strong desire to learn, innovate, and continuously challenge yourself. A positive, team-focused, results-oriented attitude, and strong collaboration skills.

Preferred additional Requirements

Familiarity with context-free grammars, e.g. ANTLR, and a good theoretical understanding of Formal Language Theory. Project experience with other programming languages such as Java, Golang, Rust, or C++. Hands-on experience with Model-Context-Protocol (MCP) integration in real-world systems
Job Type: Full-time

Pay: From $75,000.00 per year

Benefits:

Dental care Extended health care Life insurance Paid time off Stock options Vision care
Schedule:

Monday to Friday
Work Location: Hybrid remote in Calgary, AB T2P 3S8

Application deadline: 2025-07-20