AI & ML Software Engineer

Blocket AB; Mississauga; On-site; CAD 90,000 - 120,000; Full time

Job summary

A leading tech firm in Peel Region, Mississauga is seeking an AI/ML Engineer to design and implement solutions for complex signal processing tasks. The role requires at least a BS degree in a relevant field and active TS/SCI clearance. Successful candidates will collaborate with team leads to develop autonomous systems and integrate AI capabilities into existing architectures. Full relocation assistance and competitive benefits are offered, along with stock options.

Benefits

Full relocation assistance

Industry-best benefits

Stock options

Qualifications

• Hands-on experience in AI or ML in a professional environment, preferably 3-5 years.
• Strong knowledge of machine learning libraries and model deployment.
• Experience working with cloud AI platforms and real-time inference systems.

Responsibilities

• Design and implement AI/ML solutions for decision-making and processing needs.
• Work with time-series data for anomaly detection and pattern recognition.
• Collaborate on integrating AI/ML capabilities into existing architectures.

Skills

Machine learning model development

Neural network architectures

Signal analysis

Cloud AI platforms

Containerized AI models

Education

BS degree in Computer Science, Engineering, or related field

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Overview

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.

Responsibilities

• 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.

Qualifications

• 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.

Benefits

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