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채용Amgen

Principal Software Development Engineer - AI/ML

Amgen

Principal Software Development Engineer - AI/ML

Amgen

India - Hyderabad

·

On-site

·

Full-time

·

1mo ago

복지 및 혜택

Healthcare

401(k)

Equity

Learning

필수 스킬

JavaScript

TypeScript

React

Node.js

Python

REST APIs

GraphQL

Career Category

Information Systems:

Job Description

About Amgen

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller, and longer. We discover, develop, manufacture, and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

Role Description:

As a Principal Software Development Engineer/Full Stack Developer, you will build and maintain digital applications that bring Amgen’s AI/ML and GenAI solutions to life.

This role has to collaborate with Amgen’s data scientists, UX designers, and QA engineers to design secure, scalable, and user-centric products that accelerate discovery, manufacturing, and commercial analytics.

Key Responsibilities:

  • Design and implement end-to-end web applications supporting AI/ML outputs and dashboards.
  • Work across front-end (React JS) and back-end (Python / Java / Node) stacks.
  • Integrate models, APIs, and data services from Amgen’s innovation platform.
  • Collaborate with UX, QE, and Data teams to ensure performance, usability, and compliance.
  • Write clean, secure, and maintainable code; participate in code reviews and CI/CD pipelines.
  • Optimize performance, scalability, and deployment within Amgen’s AWS environment.
  • Maintain documentation and contribute to reusable frameworks.

Required Qualifications

  • 9–16 years of full-stack software development experience.
  • Strong proficiency in JavaScript / TypeScript, React JS, Node JS, Python, REST / GraphQL APIs.
  • Familiarity with cloud-native development (AWS / Docker / Kubernetes).
  • Experience integrating with data pipelines or ML models.
  • Knowledge of secure coding, testing, and deployment practices in regulated settings.
  • Excellent collaboration and problem-solving skills.

Preferred Skills

  • Exposure to GenAI / LLM-based applications (chatbots, copilots, retrieval-augmented generation).
  • Experience with MLOps and microservices architectures.
  • Understanding of CI/CD ( Jenkins / GitHub Actions ) and infrastructure-as-code.
  • Familiarity with pharma or life-sciences compliance (GxP, HIPAA) is a plus.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Amgen 소개

Amgen

Amgen

Public

A biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases.

10,001+

직원 수

Thousand Oaks

본사 위치

$138B

기업 가치

리뷰

3.6

10개 리뷰

워라밸

3.2

보상

4.1

문화

3.4

커리어

2.8

경영진

3.5

65%

친구에게 추천

장점

Excellent benefits and health benefits

Good pay and compensation

Supportive management and strong leadership

단점

Limited career growth and promotion opportunities

Work-life balance challenges and long hours

Bureaucratic processes

연봉 정보

1,244개 데이터

L2

L3

L4

L5

L6

L2 · Financial Analyst L2

0개 리포트

$94,068

총 연봉

기본급

$37,627

주식

$47,034

보너스

$9,407

$65,848

$122,288

면접 경험

5개 면접

난이도

3.0

/ 5

소요 기간

14-28주

합격률

40%

경험

긍정 20%

보통 80%

부정 0%

면접 과정

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Role-Specific Interview

5

Panel Interview

6

Offer

자주 나오는 질문

Technical Knowledge

Behavioral/STAR

Past Experience

Data Analysis/Statistics

Culture Fit