Wells Fargo
Hyderabad, India
Wells Fargo is seeking a Senior Quantitative Analytics Specialist.
Wells Fargo is seeking a hands-on experienced AI developer to contribute on projects related to development of Foundation models as well as Gen AI and Agentic applications supporting the bank across various lines of business
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Model, Methodology and Research (MMR) Team:
MMR is a specialized team which supports high priority research and development activities across Front line and second line teams within the bank. Team supports various strategic initiatives including development of Gen AI applications, in-house Large Language models, research for cutting-edge development in the industry, and Agentic development. Team also publish research papers in the top-tier conferences such as NeurIPS or ICLR.
Required Qualifications:
You will be hands-on working and contributing to the high-impact projects involving foundation models, large language models, multi-agent workflows, retrieval-augmented generation, human-in-the-loop AI, model evaluation, automation, and responsible AI deployment at enterprise scale.
Design, pre-train, fine-tune, and evaluate transformer-based, foundation, and small language models (SLMs).
Develop and deploy AI and machine learning solutions across generative AI, agentic systems, and traditional machine learning applications
Design and build LLM-powered agents and multi-agent systems capable of planning, reasoning, task orchestration, and human-in-the-loop collaboration
Monitor production models and AI systems, evaluating performance, stability, and model drift through testing and analytics frameworks
Collaborate with cross-functional teams, technical experts, and business leaders across the organization
Gain exposure to enterprise-scale AI development, governance, and risk management practices
Apply AI, machine learning, and generative AI techniques to solve complex business problems.
Build and optimize scalable model training and deployment pipelines.
Leverage distributed computing and advanced training techniques to improve model performance and efficiency.
Enhance model performance through distillation, quantization, and pruning.
Optimize inference speed, latency, throughout, and cost for production AI systems.
Posting End Date:
29 Sep 2026
*Job posting may come down early due to volume of applicants.
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
To request a medical accommodation during the application or interview process, visit
Disability Inclusion at Wells Fargo
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Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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