Job Description
Responsibilities: At the Premier Cloud Security Provider, we are working with the massive scale of network data, security data, and enterprise data every day. We are seeking out engineers with a passion to build out tools and platforms, process and analyze data at scale, and solve real-world business problems. As a software engineer for our Machine Learning platform, you have three main responsibilities: You will architect, build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving. You will apply analytical and math/statistics skills to stay on top of data and to ensure results are coherent and reliable. You will solve complex real-world business problems (e.g., threat detection, automation, and business intelligence) by working closely with various stakeholders including data scientists, product management, and product engineering. teams. You may not have any prior data science and ML background but you need to have a desire in building up knowledge in this area. For example, we expect you to have tremendous curiosity in how the data can and will be utilized by the data scientist in order to have a very effective collaboration with data scientists. Required Skills: - 5+ years of prior work experience as a Software Engineer or ML platform engineer - Very strong algorithm and programming skills in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms - Very strong Python and SQL scripting skills - 5+ year of experience using distributed data processing such as Spark, BigQuery or Apache Beam - 5+ year of experience with event messaging such as Kafka, RabbitMQ, etc - 5+ years of experience working with Docker, Kubernetes - Ability to learn, evaluate and adopt new technologies - BS Degree in Computer Science or related field Desirable Skills: - Experience with Go, C++, or Javascript - Experience with setting up SQL/NoSql database such as Postgres, MongoDB, Redis, and table schema - 3+ year of experience with ML automation platforms such as Kubeflow, Airflow or MLFlow - Experience with data serialization techniques and data stores for persisting events - Experience with Google cloud (or other public cloud) - Experience with building quality software by writing robust interfaces, considering design principles, and applying sound testing practices - Ability to lead and execute projects from start to finish - Knowledge of NLP/Text mining techniques and related open-source tools - Familiarity with networking and networking security - Excellent interpersonal, technical, and communication skills - Advanced degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Math or other quantitative fields from a reputed university (Ph.D. a plus) #LI - YK1
Employement Category:
Employement Type: Full time
Industry: Others
Role Category: Application Programming / MaintenanceBack Office Operations
Functional Area: Not Applicable
Role/Responsibilies: Sr Machine Learning Engineer - Spark, ETL,
Keyskills:
programming
data collection
data processing
Machine Learning
Python
SQL
Spark
Kafka
RabbitMQ
Docker
Kubernetes
learning
Computer Science
Go
C
Javascript
Postgres
MongoDB
Redis
Airflow
NLP
networking
interpersonal skills
technical skills
communication skills
Machine Learning
Computer Science
Electrical Engineering
Physics
Statistics
Software Engineer
ML platform engineer
algorithm
distributed data processing
BigQuery
Apache Beam
event messaging
evaluating
adopting new technologies
SQLNoSql database
table schema
ML automation platforms
Kubeflow
MLFlow
data serialization techniques
data stores
Google cloud
building quality software
writing robust interfaces
design principles
sound testing practices
Text mining techniques
networking security
Applied Math
PhD