Machine Learning Engineer - Austin, United States - Conexess

Description

Our History:
From our start in 2009, Conexess has established itself in 3 markets, employing nearly 200+ individuals nation-wide. Operating in over 15 states, our client base ranges from Fortune 500/1000 companies to mid-small range companies. For the majority of the mid-small range companies, we are exclusively used due to our outstanding staffing track record.

Who We Are:
Conexess is a full-service staffing firm offering contract, contract-to hire, and direct placements. We have a wide range of recruiting capabilities extending from help desk technicians to CIOs. We are also capable of offering project-based work.

Conexess Group is aiding a large healthcare client in their search for a Machine Learning Engineer. This is a long-term opportunity with a competitive compensation package.

**This is a hybrid position that requires a candidate local to Austin, TX**

Responsibilities:

• Establish and set up model life cycle management with tools like MLFlow, etc
• Developing and deploying Spark/Databricks jobs with enterprise tool stack including Jenkins, GitHub Actions
• Deployment utilizing containerization solutions like Docker and Kubernetes
• Experience with AWS cloud services and running Apache Spark applications.
• Experience with API development leveraging Fast API / Flask
• Must have industry experience in building Forecasting models
• Proven ability to work with a variety of data sources, including structured and unstructured data.

Qualifications:

• Any Engineering / Mathematics related undergrad degree
• 7+ years of experience in designing, building, and maintaining machine learning models and pipelines.
• Strong experience in Python (MLlib, TensorFlow, and PyTorch).
• Machine learning libraries: TensorFlow, PyTorch, Scikit-learn, Deploying and optimizing different pipelines that support various data science processes.

#LI-DB1