About ContextereContextere is an Ottawa-based AI company helping industrial and defence organizations transform operational data into actionable intelligence for technicians, operators, maintainers, and leaders. We work with global organizations including defence agencies, aerospace leaders, transportation providers, and industrial enterprises to deploy practical AI solutions that deliver measurable operational impact. Role SummaryThe Machine Learning Specialist will contribute to production AI and ML delivery from requirements and architecture through data preparation, model development, deployment, monitoring, and improvement. In this hands-on development role, this person will turn operational needs into secure, scalable, maintainable AI products that deliver measurable value in industrial and defence environments. The OpportunityThis is a critical technical role for someone who wants to shape how industrial and defence organizations apply AI in real operations. Working across software engineering, product, and customer teams, you will develop multi-faceted natural language AI/ML solutions with automated data pipelines, flexible deployment architectures, and secure trustworthy production services. You will strengthen product security, transparency, and governance while influencing technical direction through active collaboration and development. The ideal candidate combines ML and applied software-development depth with sound judgment, business awareness, and clear communication. The position offers visibility and growth through work with a dynamic team and recognized industrial and defence customers.

Key Responsibilities
Machine Learning Solution Development
· Translate business needs into ML requirements, solution designs, and scalable product applications.
· Design, test, and improve supervised, unsupervised, deep-learning, reinforcement-learning, NLP, and Generative AI solutions; run experiments and optimize model and product performance. Data and ML Pipelines
· Build and test scalable pipelines for automated data extraction, ingestion, cleaning, and validation.
· Develop and optimize multi-model ML pipelines incorporating data ingestion, chunking,



embeddings, and vector database operations to meet performance requirements. Deployment, Operations, and Quality
· Develop, deploy, and optimize scalable, reliable ML services using Docker, APIs or real-time endpoints, Kubernetes, and Azure.
· Develop techniques to monitor model performance and automate drift detection, evaluation, and retraining.
· Develop efficient and maintainable software using object-oriented design, coding standards, version control, automated testing, and continuous integration. Architecture, Security, and Governance
· Develop modular, reusable ML architectures that are flexible and scalable.
· Protect data, training artifacts, models, credentials, interfaces, and deployed services through appropriate security.
· Maintain lineage, metadata, versioning, and audit trails; apply governance for risk, security, accountability, and compliance. Collaboration and Documentation
· Collaborate across engineering, product, client, and project teams; communicate requirements, trade-offs, risks, and progress to technical and non-technical audiences.
· Maintain architecture, model, and data-lineage documentation; contribute to peer reviews of code, designs, tests, and documentation. What We’re Looking ForExperience and Education
· At least 3 years of experience designing, building, deploying, and operating production ML applications.
· Bachelor’s degree in computer science, mathematics, ML, AI, data science, or a related field; an advanced degree is an asset.
· Industrial, defence, and/or embedded-systems experience is an asset. Technical Expertise
· Expert Python and strong production software-development skills, including object-oriented and modular design, data structures, algorithms, architecture, version control,



automated testing, continuous integration, debugging, and code review; C++ is beneficial.
· Strong mathematics, statistics, data-modelling, and ML fundamentals, with hands-on experience in TensorFlow, PyTorch, scikit-learn, or comparable frameworks and architectures.
· Advanced NLP, ML computer vision, and applied Generative AI expertise, including RAG, embeddings, fine-tuning, vector databases, and LLM evaluation.
· Experience with Docker, Azure, MLOps/DataOps/DevOps, production deployment, distributed training, inference optimization, data lakes, and knowledge graphs. Professional Skills
· Strong analytical skills, systems-thinking, creative problem-solving, and ability to anticipate security gaps and failure modes in complex pipelines.
· Excellent written, verbal, presentation, and technical-writing skills for varied audiences.
· Cross-functional collaboration and peer-review skills, including giving, receiving, and applying constructive feedback.
· Ability to work independently and collaboratively, manage competing priorities, and operate in ambiguity. Why Join Contextere?At Contextere, you will not just develop software
- you will help put practical AI into the hands of the people who keep critical operations moving. This is an prospect to work at the intersection of industrial innovation, national security, and frontline workforce transformation. With Contextere, you will:
· Shape the future of AI for the technicians, operators, maintainers, and mission teams who power the physical world.
· Work directly with the leadership team in a high-trust, high-visibility role where your organization, judgment, and execution discipline will matter.
· Engage with world-class defence, aerospace, transportation, and industrial organizations solving real operational problems.
· Join a Canadian AI company at a pivotal growth stage, with the opportunity to help define a category and build lasting enterprise value.
· Make a measurable impact in a role that blends development innovation, customer interaction, and meaningful career growth.

📌 Machine Learning Specialist (Ottawa)
🏢 Contextere
📍 Ottawa