Sr Machine Learning Python / DevOps Engineer at Morgan Stanley

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Mar, 26

Salary

210000.0

Posted On

09 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, DevOps, ML Ops, Container Technologies, Cloud Technologies, ETL Pipelines, Linux, Data Science, Deep Learning, Model Monitoring, CUDA, Financial Sector, Documentation, Statistics, Automation

Industry

Financial Services

Description

Work with ML researchers to develop, productionize, and deploy ML based project for clients. Maintain and support production systems. Onboard and develop systems to help us manage and reuse ML models across the Firm with a focus on ML Ops Hack away at compiling and repackaging tricky libraries used by researchers. Find tooling and platform solutions to real-world problems and bring them into the Firm as quickly as possible with adherence to our security policies. Remain up to date on ML tools, libraries, and techniques across the Open Source and vendor landscape. Build and maintain tooling and systems to promote ML development within the firm. Create and maintain code samples to bootstrap ML practitioners so that the work done to help one team will help the next. Minimum 10 years of related technology experience Python (development, packaging, patching, etc.) Understanding of core infrastructure (hardware and software) and how it can be used to make our job easier, e.g., processor architectures, memory, load balancers, reverse proxies, automation frameworks, etc. Container technologies (Docker, podman, buildah, Kubernetes, etc.) Both with regards to packaging and runtime. At least some familiarity with cloud and cloud enablement technologies (AWS, Azure, Terraform.) Understanding of how to use modern and traditional data tiers, e.g., relational databases, object stores, graph databases. Experience designing ETL pipelines. Able to code in at least one other language: e.g. C/C++, C#, Java, Scala, Erlang, Elixir, Ruby. Linux (system level understanding, building software, debugging, etc.) Demonstrated interest in ML, e.g., small OSS projects, Kaggle, Coursera, books, blogs, podcasts. Self-starter capable of taking an idea and seeing it all the way from research to execution. Ability to clearly illustrate complex ideas using documentation and diagrams. Dask, Ray, Spark, Clustering tech (Zookeeper, consul, etc.) OSS development or enterprise Python development experience Mathematics, e.g., statistics, linear algebra Background in data science Knowledge of the latest deep learning deployment technologies (jax, openxla, etc.) Knowledge of model monitoring tools (mlflow, tensorboard, etc.) Experience with CUDA, ROCm, etc. Exposure to the financial sector (equities, fixed income, etc.) 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. 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. Expected base pay rates for the role will be between $150,000 and $210,000 per year at the commencement of employment. 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.

Responsibilities

Develop, productionize, and deploy ML-based projects for clients while maintaining and supporting production systems. Build and maintain tooling and systems to promote ML development within the firm.