Sr. Serverless Machine Learning Engineer

Agero   •  

Medford, MA

Industry: Automotive.

  •  

Less than 5 years

Posted 179 days ago

This job is no longer available.

2823

Description

Company Description:

Ahead of the Curve.

No one knows the road like Agero. For over 45 years, we have provided thesafest, smartest solutions for drivers and the companies that keep them moving. Headquartered in Medford, MA with operations throughout North America, we are trusted by more than 100 leading corporations and used by75% of the new passenger vehicles sold in the U.S.

As a result, we have become an industry leader, providing vehicle manufacturers and insurance carriers with privately labeled state-of-the-art roadside assistance plans and efficient claims management solutions. Our Roadside Assistance network protects more than 75 million drivers eachyear, providing award-winning service that helps motorists in their time ofneed while building customer loyalty for our clients.

Our commitment to our Employees:

  1. Have an Impact: Join us and Day 1, play a role in shaping our digital transformation.
  2. Grow your Career: Our focus us helping you grow the core competencies to shape your technology career
  3. Work that Matters: We are a roadside business singularly focusedon making sure our customers are quickly, safely and efficiently supported in their time of need.

You'll be making a difference at Agero. A big one. We're working withleading vehicle manufacturers and insurace carriers to drive the next generation of vehicle and mobile technology forward. Our mission? To make driving smarter - and safer - for everyone. POSITION SUMMARY: This position is responsible for cloud technologies invaried environments, including, but not limited to, AWS and Google Cloud Platforms. The Senior Serverless Machine Learning Engineer will focus ondesigning and developing automation to support continuous delivery, continuous integration processes, size and cost optimization using dynamic autoscaling techniques. The role will provide an enthusiastic focus onautomation in a fully Serverless or managed services environment

ESSENTIAL FUNCTIONS:

* Build highly parallelized, big data, machine-learning applications in thecloud.
* Design and code highly scalable, machine learning applications processing large volumes of data using serverless technologies on AWS and GCP
* Collaborate with other Machine Learning Engineers and Data Scientists in crafting and implementing your technical vision.
* Should be able to use various databases such as DynamoDB, Redshift, Aurora, Firebase, Spanner, BigQuery
* Strong understanding and working knowledge of Streaming solutions like Kinesis, IoT
* Follow agile processes with a focus on delivering production-ready testable code in small iterations.
* Participate in the entire development lifecycle, from concept to release.
* Participate in all phases of quality assurance and defect resolution.

KNOWLEDGE, SKILLS AND ABILITIES:

EDUCATION
Bachelor's Degree in Computer Science or equivalent requiredMastersDegree in Computer Science or equivalent preferred;

EXPERIENCE
* 2+ years software development experience with highly scalable systems involving machine learning and big data.
* Expertise in Serverless stacks.
* Expertise with data analysis languages such as Python, Scala, or R.
* Experience with Hadoop and Spark is a plus.
* Experience with a Cloud Computing Platform (such as AWS, Google Cloud)
* Experience with modern source control (Git)

Requirements

EDUCATION: Bachelor's Degree in Computer Science or equivalent requiredMasters Degree in Computer Science or equivalent preferred

EXPERIENCE:

* 2+ years software development experience with highly scalable systems involving machine learning and big data.
* Expertise in Serverless stacks.
* Expertise with data analysis languages such as Python, Scala, or R.
* Experience with Hadoop and Spark is a plus.
* Experience with a Cloud Computing Platform (such as AWS, Google Cloud)
* Experience with modern source control (Git)

WORKING RELATIONSHIPS: Interacts with management and staff withinthe organization.