
IT Co-Op - MLOps
Ridgefield, CT · HybridFull-time$20–33/hrSeen 1w agoSeen in employer's feed 3 days ago
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Job overview
Boehringer Ingelheim seeks an MLOps Engineer Co-Op candidate for its Central Data Science team in Ridgefield, Connecticut. The co-op supports data scientists by engineering and deploying machine learning solutions in production, including data-source automation, ML pipelines, application development, and platform and infrastructure support. The role is full-time, hybrid, and requires students to remain enrolled and live within commuting distance for the co-op.
Skills & qualifications
Skills
Qualifications
Full job description
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.
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.
As an employee of 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 Co-op role is an on-site position 2-3 days per week in our Ridgefield, CT office. Applicants will need to be located within commuting distance for the duration of the Co-op / Internship.
We look forward to receiving your application. Before applying please ensure you can commit to the following:
-Expect to be on-site for at least 3 days per week and must be located in the local area for the Co-op.
-Potential Start Dates in the application fro this role
-Co-op Students will work for at least 4 months after the start date. We may extend you up to 6 months in total depending on business needs. These are Full time positions only.
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 dependent upon 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
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Must be a current undergraduate, graduate or advanced degree student in good academic standing.
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Student must be enrolled at a college or university for the duration of the internship.
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Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale)or better (No rounding up).
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Major must be related to the field of internship
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Must have completed 12 credit hours within a related major and/or other related coursework.
Desired Experience, Skills and Abilities:
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BA/BS or MS in Computer Engineering, or another STEM field.
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Proficient in Python, SQL. Experience in scripting with Bash or PowerShell.
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Solid understanding of MLOps practices (reproducible ML, feature store use, model deployment, drift detection).
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Good knowledge of code and binary repositories (GitHub, Bitbucket, Huggingface).
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Infrastructure as a Service (IaaS) Cloud based experience in AWS.
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Infrastructure as Code (IaC) experience with AWS Cloud Formation and/or Terraform.
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Solid understanding of the software development lifecycle utilizing the DevOps framework around CI/CD.
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Good knowledge of CI/CD tools, processes, and procedures (AWS CI/CD services, Jenkins).
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Experience in data source access and automation.
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Some knowledge of Automation and Configuration Management toolsets (Ansible).
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Ability to collaborate in a team environment and excel working in a VUCA environment.
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Strong oral and written communication skills.
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Good understanding of networking and security knowledge, such as routing, firewall, VPN, TCP/IP, VPC.
Eligibility Requirements
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Must be legally authorized to work in the United States without restriction.
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Must be willing to take a drug test and post-offer physical (if required)
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Must be 18 years of age or older
JOB ID
37051
Job function
Information technology
Career level
Student roles & Internships
Organization
BI USA
Working time
Full-Time
Job flexibility
Hybrid
Boehringer Ingelheim is an equal opportunity global employer who takes pride in maintaining a diverse and inclusive culture. We embrace diversity of perspectives and strive for an inclusive environment, which benefits our employees, patients, and communities. 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
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