Senior Machine Learning Engineer - Oregon, United States - Karkidi

Description

What you will do
Let's do this. Let's change the world.

In this vital role you will bepartof the technical/engineering team, develop data flow pipelines to extract, transform, and load data from various data sources in various data format to enterprise data lake and data warehouse system in three regions in AWS, provide data analytics and predictive analysis to business users.

We look for people who can work in a team, able to mentor junior engineers, is curious to learn and able to develop data engineering and machine learning engineering solution in a fast-moving environment.

Be a key team member assisting in design and development of the data pipeline for Global Data and Analytics team
Work with Data Scientist to perform statistical analysis and model fine-tuning using test results; train and retrain system when necessary
Work with Data Scientist to analyze common features across use cases; define reusable features in feature tables
Ensure consistent feature engineering between training and model serving
Automate model monitoring, model retrain, model deployment process based on business requirement
Adhere to best practices for coding, testing and designing reusable code/component
Able to explore new tools, technologies that will help to improve ETL platform performance and machine learning operations
Participate in sprint planning meetings and provide estimations on technical implementation; Collaborate and communicate effectively with the product team
Mentor junior data/machine learning engineer
Win
What we expect of you
We are all different, yet we all use our unique contributions to serve patients.

The professional we seek will have these qualifications:

Basic Qualifications:
Doctorate degree
OR
Master's degree and 3+ years of Information Systems experience
OR
Bachelor's degree and 5+ years of Information Systems experience
OR
Associate's degree and 10+ years of Information Systems experience
Or
High school diploma / GED and 12+ years of Information Systems experience

Preferred Qualifications:
Ability to write robust code in Python, Java or R
Outstanding analytical and problem-solving skills; Ability to learn quickly and detail oriented
Familiar with PySpark data frame and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries
Familiar with Machine Learning life cycle, be able to implement feature store, MLflow, model registry, model deployment, model serving, model monitoring
Experience with machine learning operations
Deep knowledge of math, probability, statistics and algorithms
Experience with data modeling for both OLAP and OLTP databases, hands-on experience with SQL, especially SparkSQL performance tuning
Experience with software DevOps CI/CD tools, such GitLab
Experience with docker container, Kubernetes container orchestration
Experience with Apache Airflow and Apache Spark; Spark performance turning
Experience with Pharmaceutical industry, commercial operations
Excellent communicationskills and ability to work in a team
Thrive
What you can expect of us

As we work to develop treatments that take care of others, we also work to care for our teammates' professional and personal growth and well-being.

In addition to the base salary, Amgen offers a Total Rewards Plan comprising health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities including:

Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical,dental and vision cover age,life and disability insurance, and flexibles pending accounts.

A discretion ary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans and bi-annual company-wide shutdowns
Flexible work models, including remote work arrangements, where possible

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