Machine Learning Engineer

**Job Title:** Senior Machine Learning Engineer (LLM \& MLOps) **Location:** Toronto, ON **Work Model:** Hybrid (3–4 days WFO) **Experience:** 5\+ years (ML engineering experience) **Job Summary:** We are seeking a **Senior Machine Learning Engineer** with strong expertise in **Large Language Models (LLMs), Deep Learning, NLP, and MLOps** . The successful candidate will design, develop, and deploy scalable ML solutions, lead and mentor engineers, and collaborate with cross\-functional teams to deliver production\-ready AI systems that meet security, privacy, and regulatory requirements. **Key Responsibilities:** * Design, develop, and deploy **scalable and reliable machine learning solutions** with a focus on **LLMs and NLP** . * Work hands\-on with **LLM APIs** , including: + Prompt engineering + LLM agents + Response handling, optimization, and evaluation * Apply strong **software engineering best practices** , including design patterns, testing strategies, and deployment standards. * Lead and mentor **machine learning engineers and developers** , providing technical guidance and code reviews. * Collaborate with **product, engineering, DevOps, and compliance teams** to deliver end\-to\-end ML solutions. * Ensure ML systems meet **risk, privacy, and regulatory compliance** requirements. * Contribute to **DevOps and MLOps practices** , including CI/CD pipelines and production deployments. * Improve model performance, reliability, and observability in **production environments** . **Required Skills \& Qualifications:** * **3\+ years of hands\-on experience** in machine learning development. * Strong experience in **Deep Learning and Natural Language Processing (NLP)** . * Hands\-on experience working with **Large Language Model (LLM) APIs** . * Proven experience **leading or mentoring ML engineers or developers** . * Strong programming skills in **Python, Java, or C/C\+\+** . * Hands\-on experience with **cloud platforms** : AWS, GCP, or Azure. * Solid understanding of **MLOps tools and workflows** . * Experience with **DevOps practices** , including: + CI/CD pipelines + Docker\-based containerization + Kubernetes orchestration * Experience with ML frameworks such as **PyTorch, TensorFlow** , or equivalent. * Strong **communication, leadership, and collaboration skills** . **MLOps \& Orchestration Tools (Preferred):** * Experience with one or more orchestration platforms: + Apache Airflow + Kubeflow + Dagster + Flyte + Metaflow **Nice\-to\-Have Skills:** * Familiarity with **Snowflake** , Airflow, or similar **data warehousing and orchestration tools** . * Strong understanding of: + CI/CD principles + Version control systems (Git) + Production ML deployment best practices **Core Competencies:** * Strong problem\-solving and analytical skills * Ability to design **production\-grade ML systems** * Leadership and mentoring capability * Collaborative mindset across engineering and business teams * Focus on scalability, reliability, and compliance