Dice
Machine Learning Engineer / MLOps
Dice, Chicago, Illinois, United States, 60290
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Motion Recruitment Partners, LLC, is seeking the following. Apply via Dice today!
We're looking for a Machine Learning Engineer to join a startup building fraud prevention software. This role can be remote, but candidates local to the Chicago office will be preferred so they can easily attend meetings and training opportunities.
Join a close-knit group that's building a platform that can handle a high volume and complex latency fraud processing platform. In this role, you'll be building end-to-end machine learning platforms. The ideal candidate will have experience building APIs, ETL solutions, ML models, and deploying to the cloud. You'll get to work with cutting-edge tech and industry-leading tools to design and build software solutions that are fast, scalable, and flexible.
Required Skills & ExperienceMaster's degree in Computer Science, Engineering, or equivalent experience with 5+ years of experience OR bachelor's degree in Computer Science or Engineering, or equivalent experience with 7+ years of experience5+ years of experience in software engineering and software architecture background in an enterprise settingHigh volume transactional environment experienceStrong Relational database skills (SQL, JDBC - Oracle and PostgreSQL preferred)4+ years software development experience as a Python developer2+ years experience in Spark and NoSQL databases such as MapR DB, Cassandra, etc.
Daily ResponsibilitiesExperience in deploying ML models in production and familiarity with MLOpsUnderstanding in statistics and Machine Learning concepts such as model selection criteria, parameter tuning, A/B TestingBig Data Components/Frameworks such as Hadoop (MapR), Spark, etc. and the knowledge to perform ETL and compute in a distributed computing environment
BenefitsMedical InsuranceDental BenefitsVision BenefitsPaid Time Off (PTO)401(k)
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
Machine Learning Engineer / MLOps
#J-18808-Ljbffr
We're looking for a Machine Learning Engineer to join a startup building fraud prevention software. This role can be remote, but candidates local to the Chicago office will be preferred so they can easily attend meetings and training opportunities.
Join a close-knit group that's building a platform that can handle a high volume and complex latency fraud processing platform. In this role, you'll be building end-to-end machine learning platforms. The ideal candidate will have experience building APIs, ETL solutions, ML models, and deploying to the cloud. You'll get to work with cutting-edge tech and industry-leading tools to design and build software solutions that are fast, scalable, and flexible.
Required Skills & ExperienceMaster's degree in Computer Science, Engineering, or equivalent experience with 5+ years of experience OR bachelor's degree in Computer Science or Engineering, or equivalent experience with 7+ years of experience5+ years of experience in software engineering and software architecture background in an enterprise settingHigh volume transactional environment experienceStrong Relational database skills (SQL, JDBC - Oracle and PostgreSQL preferred)4+ years software development experience as a Python developer2+ years experience in Spark and NoSQL databases such as MapR DB, Cassandra, etc.
Daily ResponsibilitiesExperience in deploying ML models in production and familiarity with MLOpsUnderstanding in statistics and Machine Learning concepts such as model selection criteria, parameter tuning, A/B TestingBig Data Components/Frameworks such as Hadoop (MapR), Spark, etc. and the knowledge to perform ETL and compute in a distributed computing environment
BenefitsMedical InsuranceDental BenefitsVision BenefitsPaid Time Off (PTO)401(k)
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
Machine Learning Engineer / MLOps
#J-18808-Ljbffr