Entry Level Software Developer jobs in Canada

We are looking for an engineering professional with a solid foundation in artificial intelligence and machine learning applications to help solve challenging problems related to signal processing. The right candidate will have a high degree of drive and dedication, the ability to learn quickly, work well within a team, and hit the ground running.

• Design, develop, and implement AI/ML solutions for a wide range of decision‑making and SIGINT processing needs.
• Work with time‑series data and develop models for event characterization, pattern recognition, anomaly detection, decision making, and automated analysis of SIGINT sensor systems.
• Collaborate with team leads to integrate AI/ML capabilities into enterprise architectures, ensuring performant processing while considering accuracy, security, and maintainability.
• Enable autonomous decision‑making systems that can operate with minimal human intervention, create adaptive processing systems for dynamic environments, and discover features and infer system states from underlying data streams.
• Develop solutions for large‑scale sensing systems, implementing tailored models to deliver intelligent insights in support of critical Intelligence Community and Department of Defense missions.

• BS degree or higher in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or a related field.
• Minimum 1‑year hands‑on experience in AI or ML in a professional environment (3‑5 years preferred).
• Strong knowledge of machine‑learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit‑learn, etc.).
• Solid programming background with experience using statistical and signal analysis libraries.
• Experience with neural‑network architectures including deep learning models.
• Understanding of transformer architectures and attention mechanisms.
• Strong understanding of MLOps, deployment and processing pipelines, testing/validation.
• TS/SCI active clearance required.
• U.S. Citizenship required.
• Nice to have: Understanding of digital signal processing fundamentals.
• Experience with RFML.
• Experience with Large Language Models (LLMs) including fine‑tuning and prompt engineering.
• Knowledge of AI applications for autonomous decision‑making and analysis.
• Experience with multimodal, agentic systems using RAG, COT, or MARL approaches.
• Experience with reinforcement learning, human feedback, and related system‑learning methods.
• Experience creating and deploying containerized AI models with Docker/Kubernetes.
• Experience working with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI).
• Experience with model monitoring, A/B testing, and performance optimization.
• Experience with real‑time inference systems and low‑latency model serving.
• Knowledge of adversarial ML and AI security/robustness techniques.
• Experience with graph neural networks for network analysis.
• Experience in designing, deploying, and supporting AI or ML models for significant real‑world applications.

Full relocation assistance plus industry‑best benefits and stock options.