Schedule: M-F, core business hours – 37.5 hours per week, 7.5 hours per day The AI Engineer is responsible for designing, building, and deploying AI/ML solutions that enhance business processes, improve decision-making, and enable automation. This role combines software engineering, data science, and machine learning expertise to develop scalable AI systems in production environments. Develop end-to-end pipelines including data preprocessing, feature engineering, validation, and deployment.

Build scalable microservices or APIs to serve ML models in real time. Implement monitoring for model drift, performance, and reliability. Collaborate with data engineering teams to define data requirements.

Work with structured and unstructured datasets using Python, SQL, Spark, Pandas, etc. Ensure data quality, governance, and security Evaluate recent AI frameworks, tools, and techniques. Stay up to date with advancements in LLMs,



vector embeddings, multimodal AI, and model compression/optimization.

Work with product managers and business teams to translate business problems into AI solutions. Partner with cloud engineers and DevOps teams for scalable deployment. Communicate complex technical concepts to non-technical stakeholders.

Strong programming skills in Python (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow).

Experience with cloud platforms (AWS/GCP/Azure) and model deployment. Strong understanding of data structures, algorithms, and software engineering best practices. At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.

📌 Engineer, Technology Deployment (Toronto)
🏢 SPECTRAFORCE
📍 Toronto