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Morgan Stanley
Morgan Stanley

Leading company in the financial services industry

Generative AI Engineering Specialist (multiple roles)

职能机器学习
级别中级
地点Montreal, Quebec, Canada
方式现场办公
类型全职
发布6个月前
立即申请

必备技能

Python

JavaScript

Node.js

SQL

AWS

Linux

PyTorch

TensorFlow

Azure

Machine Learning

We are currently looking to fill multiple GenAI engineering roles across the Montreal office. The firm is heavily investing in Montreal as an AI location with roles ranging from chatbot engineering, AI solution and platform engineering to data engineering for AI projects.Different teams are hiring for various levels of experience, so whether you are only starting out, have been doing the role for a few years or you are leading a team, we want to speak with you!Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on…What you will bring to the roleAll of our potential candidates should have, at minimum, the following:Bachelor’s or a master’s degree in computer science or related field, or equivalent job experienceDeep experience (4+ years) with Python coding and developmentDemonstrated knowledge and interest in Generative Artificial Intelligence / LLMs, model training, fine tuning and related APIsSolid understanding of NLP and Artificial Intelligence / Machine Learning conceptsStrong background in LinuxThings to highlight on your resumeWhile these are not required, we are very interested in speaking with people who have exposure to the following items. Do not hesitate to highlight them on your resume!Experience with Flask, Django and/or FastAPIStrong hands-on proficiency in Python libraries like numpy, opencv, scikit-learn, pandas, matplotlib, seaborn, etc.Experience building applications using AI development services on prominent cloud platforms such as Azure Open AI, Azure AI Foundry, Azure Search, Azure Cognitive Services, AWS Bedrock, AWS Sagemaker, Google Vertex AIExperience working with Generative AI development, embeddings, fine tuning of Generative AI models.Understanding of Model Ops/ ML Ops/ LLM OpsUnderstanding of AI/ML Lifecycle and basic understanding of systems like mlflow, Dataiku,  databricks.Understanding of Machine Learning frameworks such as TensorFlow or PyTorchBroad understanding of data engineering (SQL, NoSQL, Big Data), data governance, data privacy and securityExperience with JavaScript and Node.js and other software development frameworks and librariesDemonstrated experience in DevOps, understanding of CI/ CD. Hands on experience with managing code in code repositories such as Bit Bucket and GitHubExperience designing, creating, and interfacing with Virtual Agents using Amelia, Kore.ai, Microsoft Copilot Studio or similar platformSourcing and labeling training data for ML modelsExposure to cloud environments (Docker/Kubernetes) as a user  Experience with cloud platforms such as AWS and AzureExperience working with application development teams to enable them to build AI based applicationsAbility to create code samples to be shared with application teamExperience working in a large, regulated industry such as Financial Services, Insurance etc.At Morgan Stanley Montreal, we support the Firm’s global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, data analytics, cloud engineering, cybersecurity and digital technologies. Morgan Stanley has been rooted in the Montreal community since 2008 and is considered a leading employer among the area’s highly skilled technology talent.Knowledge of French and English is required.WHAT YOU CAN EXPECT FROM MORGAN STANLEY: We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.

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关于Morgan Stanley

Morgan Stanley

Morgan Stanley is an American multinational investment bank and financial services company headquartered at 1585 Broadway in Midtown Manhattan, New York City.

10,001+

员工数

New York

总部位置

$150B

企业估值

评价

10条评价

4.1

10条评价

工作生活平衡

2.8

薪酬

4.2

企业文化

3.7

职业发展

4.1

管理层

2.9

75%

推荐率

优点

Great learning opportunities and experience

High salary and bonuses

Good team dynamics and supportive colleagues

缺点

Long hours during peak times

High stress and overwhelming environment

Work-life balance issues

薪资范围

6,221个数据点

Junior/L3

Senior/L5

Staff/L6

Junior/L3 · Data Scientist L3

0份报告

$130,639

年薪总额

基本工资

-

股票

-

奖金

-

$111,043

$150,235

面试评价

6条评价

难度

3.2

/ 5

时长

21-35周

面试流程

1

Application Review

2

HR Screen/HireVue

3

Technical/Behavioral Interviews

4

Superday/Final Round

5

Onsite Interview

6

Offer Decision

常见问题

Technical Knowledge

Behavioral/STAR

Investment/Finance Concepts

Case Study

Culture Fit