Manager, AI/ML Models - Financial Engineering & Modeling (Permanent / Contract)

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What will your typical day look like?

In this role you will help financial services industry (FSI) clients face quantitative issues with informed confidence.

Using your deep technical skills and leveraging our global network of experts, you’ll provide professional advice to our FSI clients in a wide range of situations. The result? Our clients will be better placed to take control and receive the best solutions to their complex challenges.

• Lead and oversee complex, high-impact engagements in the AI Model Risk Space, ensuring alignment with industry best practices, regulatory expectations, and emerging AI governance standards.
• Guide and mentor a team in the development, validation, and review of Large Language Models (LLMs).
• Expand your expertise across broader quantitative disciplines, with opportunities to learn and contribute to credit risk modeling, customer behavior modeling, and other advanced analytical areas.

About the team

Deloitte’s Risk, Regulatory & Forensics practice delivers highly specialized advisory solutions for companies facing critical business events where significant value is at stake, in every phase of the economic cycle.

Our work is often high profile, high impact, and highly rewarding. If you’re looking for a challenge and an opportunity to grow your career alongside the best and brightest in the industry, you’ll find it in Risk, Regulatory & Forensics at Deloitte. Broaden your skills. Broaden your reach. Broaden your career. It’s all possible at Deloitte.

Enough about us, let’s talk about you

You are someone with:

• Minimum 5-7 years of experience spent within an AI model development or model validation team at a major financial institution, showcasing a consistent record of achievements while collaborating with cross-functional teams;
• Minimum 3-5 years of relevant experience in a team leading/people management capacity;
  Solid academic background with a PhD or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, or related field;
• Knowledge of NLP, LLMs (extractive and generative), fine-tuning, development, and deployment of LLM model. Familiar with higher level trends in LLMs and open-source platforms;
• Creatively solution new features for the clients’ Generative AI offerings, including testing, evaluating and benchmarking different LLMs and toolchains;
• Significant experience and proven ability with Python, Hugging Face, TensorFlow, Keras, PyTorch or similar statistical tools;
• Excellent written and verbal communication abilities, adept at effectively documenting and conveying analysis findings;
• Exhibited a goal-oriented mindset and a strong motivation to achieve targets and make a positive impact, while consistently embodying the company's core values of trust, teamwork, and accountability;
• Canadian travel required and occasional international travel. Candidates must be able to enter the USA to work on client assignments.

Total Rewards

The salary range for this position is $101,000 - $169,000, and individuals may be eligible to participate in our bonus program. Deloitte is fair and competitive when it comes to the salaries of our people. We regularly benchmark across a variety of positions, industries, sectors, targets, and levels. Our approach is grounded on recognizing people's unique strengths and contributions and rewarding the value that they deliver.

Our Total Rewards Package extends well beyond traditional compensation and benefit programs and is designed to recognize employee contributions, encourage personal wellness, and support firm growth. Along with a competitive base salary and variable pay opportunities, we offer a wide array of initiatives that differentiate us as a people-first organization. On top of our regular paid vacation days, some examples include: $4,000 per year for mental health support benefits, a $1,300 flexible benefit spending account, firm-wide closures known as "Deloitte Days", dedicated days of for learning (known as Development and Innovation Days), flexible work arrangements and a hybrid work structure.