Machine Learning Ops Engineer

Luxoft; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

A leading international bank is seeking a data science professional to streamline and automate the data science product lifecycle. The ideal candidate will have strong Python and MLOps skills, with experience in developing and deploying models. This position offers the opportunity to work closely with financial markets and contribute to innovative solutions.

Qualifications

• 3+ years of experience developing and deploying classical supervised models.
• Proficient with main Python analytics and ML libraries (numpy, pandas, scikit-learn, keras/tensorflow/pytorch).
• Experience with MLOps platforms like MLFlow / Databricks.

Responsibilities

• Streamlines and automates data science products lifecycle from development to deployment and monitoring.
• Designs, develops and maintains tools enabling reproducible experimentation, models versioning, automated deployment.
• Provides support and guidance to other team members on MLOps best practices.

Skills

Python

MLOps

Linux

containerization

DevOps

Job description

Project description

We are a leading international bank focused on helping people and companies prosper across Asia, Africa and the Middle East.To us, good performance is about much more than turning a profit. It's about showing how you embody our valued behaviors - do the right thing, better together and never settle - as well as our brand promise, Here for good.We're committed to promoting equality in the workplace and creating an inclusive and flexible culture - one where everyone can realize their full potential and make a positive contribution to our organization. This in turn helps us to provide better support to our broad client base.About the TeamFinancial Markets (FM) has expertise combined with deep local market knowledge to deliver a variety of risk management, financing and investment solutions to our clients. The FM team offers capabilities across origination, structuring, sales, trading and research. Offering a full suite of fixed income, currencies, commodities, equities and capital markets solutions, FM has firmly established itself as a trusted partner with extensive on-the-ground knowledge and deep relationships.

Responsibilities

• Streamlines and automates data science products lifecycle from development to deployment and monitoring.
• Designs, develops and maintains tools enabling reproducible experimentation, models versioning, automated deployment, serving etc.
• Tests, refactors, optimizes, and packages the code developed by data scientists. Improves, deploys, monitors and maintains developed models.
• Builds new integrations with FM systems (PDS, ION, S2BX) allowing to publish signals generated by the data science modules.
• Provides support and guidance to other team members on MLOps best practices.

SKILLS

Must have

• -
• 3+ years of experience developing and deploying classical supervised models, ideally in on-prem environments
• Proficient with main Python analytics and ML libraries (numpy, pandas, scikit-learn, keras / tensorflow / pytorch)
• Experience with MLOps platforms like MLFlow / Databricks
• Experience with Linux (especially RedHat distribution) and version control (git)
• Experience with containerization technologies (docker/podman)
• Familiarity with DevOps pipelines (especially Azure DevOps Services)
• Eager to learn

Nice to have

• Experience in data modelling and database management. Experience managing RDBMS (preferably PostgreSQL).• Familiarity with Airflow or similar data orchestration services• Familiarity with distributed processing frameworks, esp. Hadoop and Spark/PySpark• Familiarity with kdb+/q• Familiarity with financial markets, esp. fixed income