Manager, Applied Researcher

161 Bay Street (93021), Canada, Toronto,Toronto, Ontario,Manager, Applied Researcher

About Capital One Canada

For 30 years, we've been on a mission to change banking for good. We challenge the traditional bank stereotype by integrating machine learning, conversational AI and design thinking into our core operations. We're a bank a tech company would build, where your work directly shapes innovative solutions that impact millions of Canadians.

We're driven by fearless curiosity, bold innovation, and a collective of authentic people working together to redefine what's possible. Technology isn’t just part of our strategy, it is our strategy. Everything we do serves our vision and the creation of what's next.

About the Team
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.

About the Role

In this role, you will:

• Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
• Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
• Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The ideal candidate:

• You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.

• You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• You have a deep understanding of the foundations of AI methodologies.
• You have experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
• You are an engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
• You have experience in delivering libraries, platform level code or solution level code to existing products.
• You are a professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
• You possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:

• Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research

Preferred Qualifications:

• PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
• LLM
  • PhD focus on NLP or Masters with 5 years of industrial NLP research experience
  • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
  • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
  • Publications in deep learning theory
  • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
• Optimization (Training & Inference)
  • PhD focused on topics related to optimizing training of very large deep learning models
  • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression
  • Experience optimizing training for a 10B+ model
  • Deep knowledge of deep learning algorithmic and/or optimizer design
  • Experience with compiler design
• Finetuning
  • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
  • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
  • Experience deploying a fine-tuned large language model

Working at Capital One

You’ll be empowered to take end-to-end ownership of your work and your career, backed by a high-performance, hybrid culture and holistic suite of benefits designed to support your whole self.

• Take ownership of your own potential: Whether you’re looking to upskill, pivot into new business areas, or master your craft, you’ll have access to tools and mentorship to reach your potential and define your career trajectory.
• Find your rhythm: We believe trust fosters the flexibility and autonomy required to balance personal needs with a focus on high performance. We support a hybrid model – with 3 days in the office per week – that gives room for both collaboration and personal commitments.
• Benefits built for your life: We take a holistic approach to well-being, providing support for you and those who are most important to you. This includes: full coverage for spouses, domestic partners and dependents, a one-time Work From Home allowance to build your comfortable workspace, up to $3,000 in mental health coverage and up to $5,000 in annual tuition subsidies.

You’ll find that Capital One is committed to helping you thrive and evolve every step of the way.

This posting is for an existing vacancy.

The expected annual salary range for this position is $173,000 to $197,400.This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es). Incentives could be discretionary or non-discretionary depending on the plan.

We embrace the responsible use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. However, no hiring decisions are made using AI as every hiring decision is made by our hiring managers, business interviewers, and recruitment professionals. Our teams are equipped with training that empowers them to use AI responsibly.

Capital One Canada is an equal opportunity employer committed to fostering a diverse and inclusive work environment. We consider all qualified applicants and will meet the needs of those requiring reasonable accommodations.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [email protected]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to [email protected]

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).