Senior Machine Learning Engineer, GFT

Socket.dev; Toronto; On-site; CAD 120,000 - 170,000; Full time

Job summary

Socket.dev is seeking a Senior Machine Learning Engineer to design and deploy GenAI applications at production scale from Toronto, ON. You will work with cross-functional teams to build LLM-based systems, RAG workflows, and scalable ML infrastructure, driving measurable business impact.

You will lead framing of requirements, implement robust evaluation, and ensure responsible AI practices while staying current with evolving models and tooling.

Qualifications

• 5+ years of experience in machine learning engineering with 2+ years focused on production ML systems.
• Hands-on experience building GenAI applications using LLMs, RAG, agents, or similar technologies in production environments.
• Strong proficiency in Python and modern ML frameworks (LangChain, LangGraph, Hugging Face, OpenAI API, Anthropic Claude, etc.)
• Solid understanding of LLM architectures, prompt engineering, fine-tuning, and optimization techniques
• Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes)
• Practical knowledge of MLOps practices including CI/CD, model monitoring, versioning, and deployment automation
• Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma) and semantic search systems
• Strong problem-solving skills with ability to break down complex problems into implementable solutions
• Excellent collaboration and communication skills with ability to work effectively in cross-functional teams
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)

Responsibilities

• Develop and productionize advanced GenAI and AI solutions, ensuring they address complex business challenges with measurable impact and deliver tangible ROI
• Optimize and deploy state-of-the-art ML models and AI agents, leveraging modern frameworks and best practices for scalability, reliability, and maintainability
• Contribute to experimentation and continuous improvement cycles, including robust prompt engineering, model evaluation, A/B testing, and performance optimization of production GenAI systems
• Build and maintain production-grade ML infrastructure including data pipelines, model serving endpoints, monitoring systems, and automated deployment workflows
• Implement RAG (Retrieval-Augmented Generation) systems using vector databases, semantic search, and knowledge retrieval techniques to enhance LLM capabilities
• Develop agentic AI workflows with multi-step reasoning, tool use, and orchestration to solve complex business problems autonomously
• Collaborate with product managers, data engineers, and business stakeholders to translate requirements into technical specifications and working solutions
• Write clean, maintainable, well-documented code following software engineering best practices including code reviews, testing, and version control
• Stay current with emerging GenAI technologies and research, evaluating new models, frameworks, and techniques for potential adoption
• Participate in technical design discussions and contribute to architectural decisions for GenAI applications and ML infrastructure
• Ensure responsible AI practices including bias detection, model explainability, security, privacy, and compliance with enterprise governance standards
• Document technical solutions, architectures, and processes to enable knowledge sharing and team scalability

Skills

GenAI applications

LLM

Python

LangChain

LangGraph

Hugging Face

OpenAI API

Anthropic Claude

MLOps

Vector databases

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Tools

Docker

Kubernetes

Pinecone

Weaviate

pgvector

Chroma

Job description

Job Description

What is the opportunity?

Come and be part of our innovative and high-performing GenAI and Mobile team if you are a talented, tenacious, meticulous, and results-focused individual who thrives on building production-grade GenAI applications. We are seeking an experienced Senior Machine Learning Engineer to help shape, develop, and deliver AI applications and proof-of-concepts (POCs) across diverse business lines. The successful candidate will collaborate with stakeholders to identify opportunities, develop impactful solutions, and drive the adoption of advanced AI technologies across the organization.

Are you a talented, creative, and results-driven professional who thrives on delivering high-performing GenAI applications at scale? Come join us!

Global Functions Technologies impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformational IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

As a Senior Machine Learning Engineer, you will be a key member of a team, developing and deploying large-scale GenAI applications for enterprise use cases. You will build and optimize LLM-based solutions, RAG systems, agentic workflows, and production ML infrastructure that powers effective decision-making across RBC. You will be working in a cross-functional team that supports various businesses and you will have an opportunity to work with different kinds of datasets, modern AI frameworks, and cloud-native platforms. You will collaborate with other developers, ML engineers, and business partners to deliver medium to high-complexity GenAI initiatives with measurable business impact.

What will you do?

• Develop, and productionize advanced GenAI and AI solutions, ensuring they address complex business challenges with measurable impact and deliver tangible ROI
• Optimize and deploy state-of-the-art ML models and AI agents, leveraging modern frameworks (e.g., LangChain, LangGraph, or similar) and best practices for scalability, reliability, and maintainability
• Contribute to experimentation and continuous improvement cycles, including robust prompt engineering, model evaluation, A/B testing, and performance optimization of production GenAI systems
• Build and maintain production-grade ML infrastructure including data pipelines, model serving endpoints, monitoring systems, and automated deployment workflows
• Implement RAG (Retrieval-Augmented Generation) systems using vector databases, semantic search, and knowledge retrieval techniques to enhance LLM capabilities
• Develop agentic AI workflows with multi-step reasoning, tool use, and orchestration to solve complex business problems autonomously
• Collaborate with product managers, data engineers, and business stakeholders to translate requirements into technical specifications and working solutions
• Write clean, maintainable, well-documented code following software engineering best practices including code reviews, testing, and version control
• Stay current with emerging GenAI technologies and research, evaluating new models, frameworks, and techniques for potential adoption
• Participate in technical design discussions and contribute to architectural decisions for GenAI applications and ML infrastructure
• Ensure responsible AI practices including bias detection, model explainability, security, privacy, and compliance with enterprise governance standards
• Document technical solutions, architectures, and processes to enable knowledge sharing and team scalability

What do you need to succeed?

Required Qualifications

• 5+ years of experience in machine learning engineering with 2+ years focused on production ML systems
• Hands-on experience building GenAI applications using LLMs, RAG, agents, or similar technologies in production environments
• Strong proficiency in Python and modern ML frameworks (LangChain, LangGraph, Hugging Face, OpenAI API, Anthropic Claude, etc.)
• Solid understanding of LLM architectures, prompt engineering, fine-tuning, and optimization techniques
• Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes)
• Practical knowledge of MLOps practices including CI/CD, model monitoring, versioning, and deployment automation
• Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma) and semantic search systems
• Strong problem-solving skills with ability to break down complex problems into implementable solutions
• Excellent collaboration and communication skills with ability to work effectively in cross-functional teams
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)

Preferred Qualifications

• Experience in financial services or highly regulated industries with understanding of compliance and data privacy requirements
• Knowledge of agentic AI architectures and multi-agent orchestration frameworks
• Experience with real-time streaming data and event-driven architectures
• Familiarity with distributed systems and high-scale data processing
• Experience with A/B testing frameworks and experimentation platforms
• Contributions to open-source ML/AI projects or technical blog posts
• Experience with graph databases and knowledge graph construction
• Understanding of transformer architectures and attention mechanisms

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact on enterprise AI adoption across RBC
• Work in a dynamic, collaborative, progressive, and high-performing team
• Opportunities to do challenging work and build cutting-edge GenAI solutions at scale
• Access to emerging technologies and continuous learning in the rapidly evolving AI landscape
• Exposure to diverse business problems across Risk, Finance, Compliance, and other critical functions
• Competitive compensation and benefits package

Job Skills

Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages

Additional Job Details

Address: RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-08-28

Application Deadline: 2026-09-25

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.