Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management, and wealth management services. The Firm’s employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career – a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.
Technology works as a strategic partner with Morgan Stanley business units and the world’s leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley’s sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients’ businesses-and to our own.
Team Profile:
Transformation builds the technological capabilities and connections that keep Morgan Stanley thriving, giving the Firm the agility and stability to perform in all market conditions. The division is comprised of Centers of Excellence across Agile / Front-to-Back platform operations, Artificial Intelligence / Machine Learning, Cloud, and Automation; Technology Business Development, which manages Morgan Stanley’s strategic relationships with external technology companies; and the Innovation Office, which focuses on removing barriers to innovation and accelerating time to value.
Position Description:
The Platform Engineering Team is seeking a Linux Python developer and DevOps engineering specialist to support machine learning scientists and help expand and extend machine learning technology throughout the firm.
This position is ideal for a solid technologist who:
Enjoys a “Jack of all trades” role. Doing a bit of development, system administration, DevOps/MLOps, productionization work, prototyping, support, integration, onboarding, code review, library maintenance, documentation, etc.
- Is interested in being in the middle of all levels of the technology stack. Working with infrastructure as well as customer facing products. Who wants to help build out the technology needed to deploy large models like GPT-3 and Bloom.
- Is interested in contributing to open source software through a Morgan Stanley and/or FINOS project or directly to 3rd party projects
- Has an infrastructure background but is looking to move up or sideways in the stack.
Responsibilities:
- Work with researchers to restructure, improve, and productionize projects
- Promote best practices and develop technologies to reduce complexity within the developer workflow
- Profiling and reworking code / workflows of existing projects to minimize resource consumption, improve performance, minimize time to market, and increase stability
- Building PoCs with OSS onprem and in cloud to evaluate the latest technologies
- Helping researchers, ML engineers, and other developers by improving the technology stack, writing documentation, publishing examples, etc.
- Help guide and promote adoption of model ops throughout the firm
- Evaluate new vendor technologies
Qualifications:
Required Skills:
- 5 years’ experience in the following topics- System administrator level familiarity with Linux or other *nix operating system
- Hands on experience with container technologies (Docker, podman, buildah, Kubernetes, etc.) regarding packaging and runtime
- Basic familiarity with cloud and cloud enablement technologies (AWS, Azure, Terraform)
- Python development including building and packaging of projects
- DevOps (IE usage of CI/CD pipelines, software deployment, container orchestration, etc.)
- SCM workflows in medium to large teams
- Excellent oral and written communication skill
- Self-motivated and able to work in a global, distributed team
Nice to have:
- Experience with compiled languages such as C/C++ and how libraries work
- AI / ML familiarity
- Strong fundamentals in Unix system calls, shell scripting, IPC, and distributed systems
- Familiarity with authentication systems such as OIDC
- ModelOps / MLOps experience
- Plotly Dash experience
- Dash, Spark, Ray, etc. experience
Expected base pay rates for the role will be between $100,000 to $150,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley’s goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).