Salesforce Principal/Lead/Senior Software Engineer - ML Infrastructure 

United States, Washington, Bellevue 

730625246

Job Category

Software Engineering

Job Details

What you’ll do:

• Design and deliver scalable generative AI services that can be integrated with many applications, thousands of tenants, and run at scale in production.

• Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring and root cause analysis.

• Participate in periodic on-call rotations and be available for critical issues.

• Partner with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production

• Participate in meal conversations with your team members about really important topics, such as: Should the cuteness of panda bears be a factor in their survivability? Is love a decision tree or a regression model? How far ahead would society be today if we had 12 fingers instead of 10?

Required Skills:

• 8+ years of industry experience of ML engineering in building AI systems and/or distributed services.

• Bachelors (or) Masters degree in Computer Science, Software Engineering, or related STEM field with strong competencies in algorithms, data structures and software design.

• Experience building distributed microservice architecture on AWS, GCP or other public cloud substrates

• Experience using modern containerized deployment stack using Kubernetes, Spinnaker, and other technologies

• Proven ability to implement, operate, and deliver results via innovation at large scale

• Strong programming expertise in JVM-based languages (Java, Scala) and Python.

• Experience with distributed, scalable systems and modern data storage, messaging and processing frameworks, including Kafka, Spark, Docker, Hadoop, etc.

• Grit, drive and a strong feeling of ownership coupled with collaboration and leadership.

Preferred Skills:

• Understanding of MLOps/ML Infra workflows, processes and ML components

• Strong experience building and applying machine learning models for business applications

• Working or academic knowledge with Sagemaker, Tensorflow, Pytorch, Triton, Spark, or equivalent large-scale distributed Machine Learning technologies

• Fantastic problem solver; ability to solve problems that the world has not solved before

• Excellent written and spoken communication skills

• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams

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