This role focuses on optimizing large-scale financial modeling applications by implementing MLOps practices and maintaining end-to-end pipelines on AWS.
Description: We are seeking an experienced and highly skilled AWS Full Stack ML Engineer to operationalize and optimize our large-scale financial modeling applications. This role requires a unique blend of expertise in machine learning, software engineering, and AWS cloud infrastructure, with a strong focus on implementing robust MLOps practices to ensure scalability, reliability, and cost-efficiency. The ideal candidate will bridge the gap between data science and production systems, transforming data science prototypes into secure, high-performance, and compliant solutions in a fast-paced financial environment. Key Responsibilities Implement MLOps and CI/CD: Design, build, and maintain end-to-end MLOps pipelines for the continuous integration, training, deployment, and monitoring of ML models on AWS. System Design and Integration: Reengineer large scale model development code (from data scientists) and model application code (from software engineers) and seamlessly integrate into unified, production-ready systems. Education: A Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field Certifications (Preferred): AWS Certified Machine Learning - Specialty certification, AWS Certified Solutions Architect – Associate, or other relevant cloud certifications
Top Skills
AWS
Ci/Cd
Machine Learning
Mlops
Software Engineering
Similar Jobs
Information Technology • Consulting
Lead the development of data pipelines and transformations in Azure Databricks, converting Scala programs to PySpark while leveraging various Azure technologies.
Top Skills:
AdfAzure Data Lake Gen 2Azure DatabricksDelta LakePysparkPythonSparkSynapse Analytics
Information Technology • Consulting
The Senior Azure Data Engineer will manage data ETL processes, mentor junior staff, and work on cloud technologies in Azure. Required experience includes Datawarehouse expertise.
Top Skills:
AdfAzureDatabricksDatawarehousePysparkPython
Information Technology • Consulting
The Big Data Lead will manage database development, ETL/ELT processes, and data warehousing, optimizing performance and ensuring data pipelines work reliably.
Top Skills:
AWSAws GlueAws S3AzureAzure BlobAzure Data FactoryAzure DevopsGitJenkinsOracleSnowflakeSQLTalendTeamcity
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
