Finance Digital Transformation - Senior Machine Learning Engineer

Austin, TX, US • Posted 1 hour ago • Updated 1 hour ago
Full Time
On-site
Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

  • Business Process
  • Finance
  • Regulatory Compliance
  • Software Engineering
  • Data Science
  • Debugging
  • Testing
  • Version Control
  • Code Review
  • Continuous Delivery
  • Machine Learning Operations (ML Ops)
  • Kubernetes
  • Cloud Computing
  • Algorithms
  • Shipping
  • Generative Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Evaluation
  • Corporate Finance
  • Accounting
  • Supply Chain Management
  • Sarbanes-Oxley
  • Profit And Loss

Summary

magine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders. \\n\\nAs a senior machine learning engineer in Finance, you'll play an integral and global role in building the platform, data foundations, and services used for transforming Finance's organization.

You'll learn intra-team and business process to build infrastructure and services enabling an effective Machine Learning practice. You will help lead the charge by developing strong AIML processes and extending platforms in a dynamic environment where you will deal with unique challenges specific to Finance organizations, such as SOX and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.\n

Bachelors degree (CS, data science, engineering, or similar) with 7+ years experience\nDemonstrated experience improving and extending existing AIML platforms and services\nHands-on ML platform experience: feature stores, registries, experiment tracking, and model serving\nStrong debugging and operational instincts\nValues engineering standards; modularity, testing, version control, and code review \nCI/CD and MLOps experience strengthening existing pipelines; familiar with GitOps \nProduction Kubernetes and cloud platform experience \nWorking knowledge of ML algorithms; experience shipping generative AI and agentic solutions

Experience inheriting and modernizing legacy ML infrastructure without disrupting existing users\nLLMOps familiarity - evaluation pipelines, RAG infrastructure, prompt versioning, and production guardrails\nBackground in corporate finance, accounting, or supply chain; understanding of SOx, P&L, and close processes\nFront-end experience for extending internal tooling and platform UIs a plus
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: ec21866132a39fa7fe18778a9aa749c1
  • Posted 1 hour ago
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