Prodigal
Software Engineer - Machine Learning
Prodigal, Mountain View, California, us, 94039
[Full Time] Software Engineer - Machine Learning at Prodigal (United States)Software Engineer - Machine Learning
Prodigal United StatesDate Posted: 02 Aug, 2023Work Location: Mountain View, United StatesSalary Offered: Not SpecifiedJob Type: Full TimeExperience Required: No experience requiredRemote Work: NoStock Options: NoVacancies: 1 availableWe are a fast-growing Bay Area-based startup backed by leading investors like Menlo Ventures, Accel, and Y-Combinator. We create AI and ML-powered software for the finance and lending industries, focused on repayment and debt recovery. Our products use AI to create next-generation speech analytics that support real-time agent guidance, automated notes after conversations, and call analysis for quality assurance and compliance.We are looking for a scrappy and detail-oriented Machine Learning Engineer to join our Data Science and Machine Learning team. In this role, you will work closely with data scientists and engineers to deploy and optimize ML models in production.Responsibilities:
Collaborate with fellow data scientists to implement and productionize machine learning modelsWrite clean, scalable code to integrate models into our tech stackPerform model evaluations and testing to ensure robust, accurate performanceMonitor models post-deployment and tweak as needed to improve metricsTroubleshoot issues with model pipelines and infrastructureContribute to the improvement of our ML architecture and frameworksPrototype and fine-tune LLMsRequirements:
6+ months of industry experience in a ML engineering roleProficiency in Python; experience with frameworks like PyTorchUnderstanding of ML fundamentalsAbility to debug and optimize model performanceStrong communication skills and ability to work cross-functionallyAttention to detail with a passion for metrics and measurementExperience deploying models on AWS or other cloud platforms (preferred)BS/MS degree in Computer Science, Statistics, Math or related fieldWhat will you do:
30 Days
Onboard and get familiar with our company systems and tech stackReview existing ML pipelines and models in productionSetup development environment on AWS and reproduce/re-train existing modelsCreate your first PR60 Days
Take ownership of maintaining and improving 1-2 existing modelsTake part in on-call rotations and troubleshoot issues in a timely mannerContribute to ML design discussions on new projectsPrototype and fine-tune ML models on AWS90 Days
Demonstrate impact by shipping high-quality projectsDeploy an ML model end-to-endFine-tune LLMs on AWS using compute efficient techniquesIdentify areas for improvement and growthAbout you:
You're the type of engineer who digs into problems hands-on and fixes things. You can focus on the small details but also see the full picture. You get excited when you figure out hard ML challenges. You can geek out with fellow data scientists but also explain things simply to other teams. You're always learning - whether it's the latest research or new engineering skills.If you want to leave generic behind and grow your expertise in an exciting startup environment, we want to hear from you!To learn more about us - please visit our website.About Prodigal
Lending Intelligence Software
Company Size:
51 - 250 PeopleYear Founded:
2018Country:
United StatesCompany Status:
Actively Hiring#J-18808-Ljbffr
Prodigal United StatesDate Posted: 02 Aug, 2023Work Location: Mountain View, United StatesSalary Offered: Not SpecifiedJob Type: Full TimeExperience Required: No experience requiredRemote Work: NoStock Options: NoVacancies: 1 availableWe are a fast-growing Bay Area-based startup backed by leading investors like Menlo Ventures, Accel, and Y-Combinator. We create AI and ML-powered software for the finance and lending industries, focused on repayment and debt recovery. Our products use AI to create next-generation speech analytics that support real-time agent guidance, automated notes after conversations, and call analysis for quality assurance and compliance.We are looking for a scrappy and detail-oriented Machine Learning Engineer to join our Data Science and Machine Learning team. In this role, you will work closely with data scientists and engineers to deploy and optimize ML models in production.Responsibilities:
Collaborate with fellow data scientists to implement and productionize machine learning modelsWrite clean, scalable code to integrate models into our tech stackPerform model evaluations and testing to ensure robust, accurate performanceMonitor models post-deployment and tweak as needed to improve metricsTroubleshoot issues with model pipelines and infrastructureContribute to the improvement of our ML architecture and frameworksPrototype and fine-tune LLMsRequirements:
6+ months of industry experience in a ML engineering roleProficiency in Python; experience with frameworks like PyTorchUnderstanding of ML fundamentalsAbility to debug and optimize model performanceStrong communication skills and ability to work cross-functionallyAttention to detail with a passion for metrics and measurementExperience deploying models on AWS or other cloud platforms (preferred)BS/MS degree in Computer Science, Statistics, Math or related fieldWhat will you do:
30 Days
Onboard and get familiar with our company systems and tech stackReview existing ML pipelines and models in productionSetup development environment on AWS and reproduce/re-train existing modelsCreate your first PR60 Days
Take ownership of maintaining and improving 1-2 existing modelsTake part in on-call rotations and troubleshoot issues in a timely mannerContribute to ML design discussions on new projectsPrototype and fine-tune ML models on AWS90 Days
Demonstrate impact by shipping high-quality projectsDeploy an ML model end-to-endFine-tune LLMs on AWS using compute efficient techniquesIdentify areas for improvement and growthAbout you:
You're the type of engineer who digs into problems hands-on and fixes things. You can focus on the small details but also see the full picture. You get excited when you figure out hard ML challenges. You can geek out with fellow data scientists but also explain things simply to other teams. You're always learning - whether it's the latest research or new engineering skills.If you want to leave generic behind and grow your expertise in an exciting startup environment, we want to hear from you!To learn more about us - please visit our website.About Prodigal
Lending Intelligence Software
Company Size:
51 - 250 PeopleYear Founded:
2018Country:
United StatesCompany Status:
Actively Hiring#J-18808-Ljbffr