Co-Op IT - MLOps Engineer - 1 role - Boehringer Ingelheim
Ridgefield, CT
About the Job
Description
Boehringer Ingelheim is currently seeking a talented and innovative MLOps Engineer Co-Op candidate to join Central Data Science team at our Ridgefield, CT facility. As an MLOps Engineer Co-Op, you will work on a global strategic initiative to make better use of our data and enhance our ability to make data driven decisions. You will work closely with data scientists to engineer and deploy machine learning solutions in production environments. You will help the team shape, develop, and execute complex analytic solutions that will transform the healthcare industry.
At Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.
This role is an on-site position 2-3 days per week in our Ridgefield, CT office depending upon business needs. Applicants will need to be located within commuting distance for the duration of the Co-op / Internship.
_Co-ops before applying ensure you can commit to the following:_
1. _Expect to be on-site for at least 3 days per week and must be located in the local area for the Co-op._
2. _You can start on the following dates: Dates are not flexible_ _January 6, January 21 or February 3._
3. _You can work full-time and for at least 4 months after the start date. We can extend you up to 6 months in total._
Compensation Data
This position offers an hourly rate typically between $20/ hour and $33/ hour commensurate to the level of degree program in which an applicant is actively enrolled. For an overview of our benefits please click here. Rate is based on Degree level.
Duties & Responsibilities
The primary focus of the MLOps Engineer Co-Op candidate will be to provide engineering support to data scientists by developing secure, automated, scalable, maintainable production-grade solutions for deployment. Responsibilities include data source automation, ML pipeline development, app development, platform and infrastructure support.
Requirements
+ Must be a current undergraduate, graduate or advanced degree student in good academic standing.
+ Student must be enrolled at a college or university for the duration of the internship / co-op
+ Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale)preferred.
+ Major or minor in related field of internship
+ Undergraduate students must have completed at least 12 credit hours at current college or university.
+ Graduate and advanced degree students must have completed at least 9 credit hours at current college or university.
+ Onsite/Flex*: This position is site based with flexibility for remote working. Working onsite a minimum of 2-3 days per week is required. Remote working norms will be clarified during the interview process.
Eligibility Requirements
+ Must be legally authorized to work in the United States without restriction.
+ Must be willing to take a drug test and post-offer physical (if required)
+ _Must be 18 years of age or older_
Desired Skills, Experience and Abilities
+ Pursuing BA/BS or MS in Computer Engineering, or another STEM field.
+ Proficient in Python, SQL. Experience in scripting with PowerShell, Ruby, or Bash
+ Good knowledge of code and binary repositories (GitHub or Bitbucket)
+ Infrastructure as a Service (IaaS) Cloud based experience in AWS.
+ Infrastructure as Code (IaC) experience with AWS Cloud Formation and/or Terraform.
+ Solid understanding of the software development lifecycle utilizing the DevOps framework around CI/CD.
+ Good knowledge of CI/CD tools, processes, and procedures (AWS CI/CD services, Jenkins)
+ Experience in data source access and automation.
+ Some knowledge of Automation and Configuration Management toolsets (Ansible)
+ Ability to collaborate in a team environment and excel working in a VUCA environment.
+ Strong oral and written communication skills. Preferred Candidate May Also Have: Experience of distributed computing (Hive/Hadoop) is a plus.Good understanding of networking and security knowledge, such as routing, firewall, VPN, TCP/IP, VPC.Experience or coursework in machine learning and/or deep learning packages.
All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.
Boehringer Ingelheim is currently seeking a talented and innovative MLOps Engineer Co-Op candidate to join Central Data Science team at our Ridgefield, CT facility. As an MLOps Engineer Co-Op, you will work on a global strategic initiative to make better use of our data and enhance our ability to make data driven decisions. You will work closely with data scientists to engineer and deploy machine learning solutions in production environments. You will help the team shape, develop, and execute complex analytic solutions that will transform the healthcare industry.
At Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.
This role is an on-site position 2-3 days per week in our Ridgefield, CT office depending upon business needs. Applicants will need to be located within commuting distance for the duration of the Co-op / Internship.
_Co-ops before applying ensure you can commit to the following:_
1. _Expect to be on-site for at least 3 days per week and must be located in the local area for the Co-op._
2. _You can start on the following dates: Dates are not flexible_ _January 6, January 21 or February 3._
3. _You can work full-time and for at least 4 months after the start date. We can extend you up to 6 months in total._
Compensation Data
This position offers an hourly rate typically between $20/ hour and $33/ hour commensurate to the level of degree program in which an applicant is actively enrolled. For an overview of our benefits please click here. Rate is based on Degree level.
Duties & Responsibilities
The primary focus of the MLOps Engineer Co-Op candidate will be to provide engineering support to data scientists by developing secure, automated, scalable, maintainable production-grade solutions for deployment. Responsibilities include data source automation, ML pipeline development, app development, platform and infrastructure support.
Requirements
+ Must be a current undergraduate, graduate or advanced degree student in good academic standing.
+ Student must be enrolled at a college or university for the duration of the internship / co-op
+ Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale)preferred.
+ Major or minor in related field of internship
+ Undergraduate students must have completed at least 12 credit hours at current college or university.
+ Graduate and advanced degree students must have completed at least 9 credit hours at current college or university.
+ Onsite/Flex*: This position is site based with flexibility for remote working. Working onsite a minimum of 2-3 days per week is required. Remote working norms will be clarified during the interview process.
Eligibility Requirements
+ Must be legally authorized to work in the United States without restriction.
+ Must be willing to take a drug test and post-offer physical (if required)
+ _Must be 18 years of age or older_
Desired Skills, Experience and Abilities
+ Pursuing BA/BS or MS in Computer Engineering, or another STEM field.
+ Proficient in Python, SQL. Experience in scripting with PowerShell, Ruby, or Bash
+ Good knowledge of code and binary repositories (GitHub or Bitbucket)
+ Infrastructure as a Service (IaaS) Cloud based experience in AWS.
+ Infrastructure as Code (IaC) experience with AWS Cloud Formation and/or Terraform.
+ Solid understanding of the software development lifecycle utilizing the DevOps framework around CI/CD.
+ Good knowledge of CI/CD tools, processes, and procedures (AWS CI/CD services, Jenkins)
+ Experience in data source access and automation.
+ Some knowledge of Automation and Configuration Management toolsets (Ansible)
+ Ability to collaborate in a team environment and excel working in a VUCA environment.
+ Strong oral and written communication skills. Preferred Candidate May Also Have: Experience of distributed computing (Hive/Hadoop) is a plus.Good understanding of networking and security knowledge, such as routing, firewall, VPN, TCP/IP, VPC.Experience or coursework in machine learning and/or deep learning packages.
All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.
Source : Boehringer Ingelheim
