This role is for you if you are passionate about software engineering and are also familiar with the data science stack. It requires close collaboration with data scientists so a basic understanding of machine learning concepts is also very useful.
What you’ll do/ Responsibilities:
Design and build our Machine Learning Platform to help data scientists productionize their models and features faster.Engineer high-reliability, high-performance services for sophisticated ML-driven functionality.Collaborate with data scientists to optimize ML models for high-throughput, low-latency use cases.Build internal tools and interfaces to improve the productivity of the team and improve the accessibility of our products.
What you’ll need/ Requirements:
At least 5 years as a software engineer.Experience with Go, Python, and Java, and fluent in at least one of these languages. Good understanding of algorithms and data structures, design patterns.Passionate about Agile software development practices such as test-driven development, pair programming, etc.Experience with relational databases. Experience with non-relational databases is a plus.Experience with cloud environments and cloud deployment technology (Terraform, Kubernetes, Helm) is a huge plus.Proven track-record building large-scale, high-throughput, low-latency production systems. Experience with web services and microservice architectures is a plus.Experience with modern Web development (full stack) is a plus.
Either (or both) of:Data science knowledge and familiarity with ML libraries such as Pandas, Scikit, Tensorflow, xgboost, Keras.Experience developing for and debugging Big Data and stream processing frameworks such as Spark, Kafka, and Flink. Experience with ML frameworks such as TFX, Kubeflow, and MLflow is a plus.