indeed
Machine Learning Engineer, Associate Director
Fitch Group
Toronto, CAN
Full Time
Lead
Hybrid
1 weeks ago
Machine LearningPythonPyTorchLarge Language ModelsRAGAgentic Workflows
Free
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Machine LearningPythonPyTorch
About the Role
Fitch Ratings is seeking a Machine Learning Engineer to join its new AI Innovation team in Toronto, building generative AI systems and agentic workflows for financial analysis. The role involves developing production ML systems, implementing RAG architectures, and working with LLMs.
Key Skills for This Role
Machine LearningPythonPyTorchLarge Language ModelsRAGAgentic Workflows
Responsibilities
- Build and deploy production ML systems including generative AI solutions, agentic workflows, and intelligent platforms using Python, PyTorch, and modern ML frameworks
- Implement AI solutions in collaboration with product teams to integrate ML capabilities into flagship Fitch products and workflows
- Develop scalable ML infrastructure and workflows including robust APIs (FastAPI), data pipelines (Airflow), and cloud services (AWS/Azure)
- Support and improve production ML solutions by maintaining SLAs, using metrics to evaluate and guide improvements, and monitoring model performance
- Experiment with emerging AI technologies including generative AI frameworks, LLMs, RAG architectures, and agentic workflows
- Collaborate effectively across teams, communicate ML concepts to diverse stakeholders, and partner with senior engineers to design scalable architectures
- Champion quality and best practices including code quality, automated testing, source version control, optimization, and containerization
- Learn, grow, and contribute to team culture by seeking feedback, embracing mentorship, and sharing learnings
Requirements
- 3+ years of professional experience as an AI/ML engineer building production quality solutions
- Strong Python development skills with adherence to software development fundamentals
- Hands on experience building generative AI frameworks, working with large language models, and fine tuning LLMs
- Working knowledge of ML algorithms including multi class classification, decision trees, support vector machines, and neural networks
- Practical knowledge of AWS and Azure infrastructure and services
- Track record of integrating AI and ML solutions into existing workflows, products, and systems
- Experience building or enhancing search systems and information retrieval capabilities
- Experience or strong familiarity with containerization technologies like Docker, Kubernetes, AWS EKS
- Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics, or related technical field (Master's or higher strongly preferred)
Full Job Posting
Machine Learning Engineer – AI Innovation Teams
- Fitch Ratings is seeking a Machine Learning Engineer to join our new AI Innovation teams in Toronto—where we're building the AI powered future of financial analysis from the ground up.
- This is about building and shipping real generative AI systems, agentic workflows, and intelligent platforms that will transform how credit analysis happens.
- As an ML Engineer, you'll be hands on building sophisticated ML systems, working directly with cutting edge technologies, learning from exceptional senior engineers, and contributing to solutions that will have measurable impact.
What We Offer
- Hands on experience with cutting edge ML technology – Work directly with the latest LLMs and foundation models, implement RAG architectures, build agentic systems, fine tune neural networks, and leverage enterprise scale GPU clusters and cloud infrastructure.
- Build real ML systems with measurable impact – Develop production generative AI capabilities, intelligent automation, and ML solutions that analysts and financial professionals use daily.
- Accelerate your ML career – Work alongside senior ML engineers and technical leaders who will mentor you, review your code, and help you grow.
- Toronto's world class AI ecosystem – Be part of one of the world's premier AI research hubs, attend cutting edge ML meetups and conferences, connect with Vector Institute researchers.
- Greenfield innovation with enterprise backing – Build net new ML systems from scratch with the freedom to experiment and learn, backed by compute resources, training budgets, and organizational support.
- Continuous learning and growth – Conference attendance, training budgets, access to the latest research and tools, and a culture that values experimentation and learning from failures.
- High visibility and clear growth path – Contribute to high impact projects with visibility to senior leadership; clear advancement opportunities to Senior ML Engineer roles.
We'll Count on You To
- Build and deploy production ML systems – Develop generative AI solutions, agentic workflows, and intelligent platforms using Python, PyTorch, modern ML frameworks, and large language models.
- Implement AI solutions in collaboration with product teams – Work closely with or as part of product squads to integrate ML capabilities into flagship Fitch products and workflows.
- Develop scalable ML infrastructure and workflows – Build robust APIs (FastAPI, etc.) for model deployment, implement data pipelines using orchestration platforms (Airflow), leverage cloud services (AWS/Azure) for ML infrastructure.
- Support and improve production ML solutions – Help maintain SLAs for AI applications, use metrics to evaluate and guide improvements to existing ML solutions, monitor model performance.
- Experiment with emerging AI technologies – Explore generative AI frameworks, work with LLMs, implement RAG architectures, experiment with agentic workflows.
- Collaborate effectively across teams – Communicate ML concepts to diverse stakeholders, work with data scientists to identify innovative solutions, partner with senior engineers to design scalable architectures.
- Champion quality and best practices – Adhere to software and ML development fundamentals including code quality, automated testing, source version control, optimization, and containerization (Docker, Kubernetes/AWS EKS).
- Learn, grow, and contribute to team culture – Actively seek feedback, embrace mentorship, share learnings with the team, experiment boldly, learn from failures.
What You Need to Have
- Solid ML engineering foundation – 3+ years of professional experience as an AI/ML engineer building production quality solutions.
- Strong Python development skills – Experience developing production quality Python code with strong adherence to software development fundamentals.
- Generative AI and LLM experience – Hands on experience building generative AI frameworks, working with large language models, leveraging and/or fine tuning LLMs.
- ML algorithm proficiency – Working knowledge of ML algorithms including multi class classification, decision trees, support vector machines, and neural networks.
- Cloud platform knowledge – Practical knowledge of AWS and Azure infrastructure and services (e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage).
- Experience integrating AI solutions – Track record of integrating AI and ML solutions into existing workflows, products, and systems.
- Search and information retrieval experience – Experience building or enhancing search systems and information retrieval capabilities.
- Containerization exposure – Experience or strong familiarity with containerization technologies like Docker, Kubernetes, AWS EKS.
- Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics, or related technical field (Master's or higher strongly preferred).
What Would Make You Stand Out
- Advanced agentic workflow experience – Hands on experience building sophisticated agentic workflows powered by language models.
- Document and content systems experience – Experience developing or integrating ML functionality for document management systems, content platforms, or document intelligence solutions.
- Prototype to production experience – Experience supporting prototyping teams and enabling seamless transitions from experimental proof of concept to production deployment.
- Strong collaboration and communication skills – Proven ability to work effectively in distributed team environments, communicate technical concepts clearly.
- Cross functional team experience – Track record of working successfully with product managers, business stakeholders, and engineers from different disciplines.
- Full stack or polyglot programming – Experience working in Java and/or JavaScript codebases in addition to Python.
- Financial services knowledge – Familiarity with credit ratings agencies, regulatory requirements, financial data products, or analytical workflows.
- Passion for ML driven outcomes – Genuine enthusiasm for using data and ML to drive better business outcomes.
- Code quality advocacy – Strong advocate of good code quality and architectural practices.
- Toronto AI/ML community interest – Interest in participating in Toronto's AI/ML engineering or research communities.
About Fitch Group
- Fitch Group is a global leader in financial information services with operations in more than 30 countries.
- Wholly owned by the Hearst Corporation, we are comprised of three main businesses: Fitch Ratings | Fitch Solutions | Fitch Learning.
- Fitch is committed to providing global securities markets with objective, timely, independent and forward looking credit opinions.
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