Machine Learning Engineer
Malvern, PA
Local Only
Full Time
$100k - $140k
Our client is looking to hire a Machine Learning Engineer role for their Data Science & Advanced Analytics team sitting in their Wayne, PA office. This role is responsible for supporting Artificial Intelligence, Machine Learning, and Data Science solutions for a Healthcare company. This position is FULLY remote. The tech stack will include but is not limited to: Python, PySpark, TensorFlow, AWS, SQL, and various other Machine Learning/ AI tools.
You will work on one of the richest data sets in U.S. finance while gaining specialization in deep learning, active learning, and classical machine learning. This role gives you limitless cloud computing resources to deliver business impact through implementation of a large pipeline of AI models.
Candidates must live within a reasonable distance of the Wayne, PA office and be willing to work onsite 3 days/week.
Required Skills:
You will work on one of the richest data sets in U.S. finance while gaining specialization in deep learning, active learning, and classical machine learning. This role gives you limitless cloud computing resources to deliver business impact through implementation of a large pipeline of AI models.
Candidates must live within a reasonable distance of the Wayne, PA office and be willing to work onsite 3 days/week.
Required Skills:
- 2+ years of full-time, professional experience in a data science or machine learning based role
- Experience building automated processes that are supportable, monitored, and enterprise-scale
- Expert level experience coding in Python
- Strong experience working with PySpark (preferred) or Spark
- Experience working with and integrating services from popular ML packages such as Keras, Tensorflow,, XGBoost, SciKit Learn
- Above average capabilities with cloud computing techniques or tools such as S3, EC2, EMR, SageMaker, ECS, Lambda, IAM
- SQL design and development skills
- Experience building/consuming REST web services
- Experience working on multi-disciplinary teams
Posted by: Caroline Stranieri