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채용Amgen

Senior Associate, Agents/Chatbots IC

Amgen

Senior Associate, Agents/Chatbots IC

Amgen

India - Hyderabad

·

On-site

·

Full-time

·

1mo ago

필수 스킬

Machine Learning

MLOps

Career Category

Information Systems:

Job Description

Join Amgen’s Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.

Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Senior Associate, Agents/Chatbots IC

What you will do

Let’s do this. Let’s change the world. In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production

  • Collaborate with data scientists to develop, train, and evaluate machine learning models.
  • Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
  • Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
  • Implement DevOps/MLOps standards to automate ML workflows and improve efficiency.
  • Develop and implement monitoring systems to track model performance and identify issues.
  • Conduct A/B testing and experimentation to optimize model performance.
  • Work closely with data scientists, engineers, and product teams to deliver ML solutions.
  • Stay updated with the latest trends and advancements

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.

Basic Qualifications:

  • Master’s degree with 5+ years of experience in Computer Science, IT or related field

Or

  • Bachelor’s degree with 5-9 years of experience in Computer Science, IT or related field
  • Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Preferred Qualifications:

  • Solid foundation in machine learning algorithms and techniques
  • Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
  • Proficiency in Python and relevant ML libraries (e.g., Tensor Flow, Py Torch, Scikit-learn)
  • Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and social skills

Good-to-Have Skills:

  • Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
  • Experience with data engineering and pipeline development
  • Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
  • Knowledge of NLP techniques for text analysis and sentiment analysis
  • Experience in analyzing time-series data for forecasting and trend analysis

Soft Skills:

  • Excellent analytical and troubleshooting skills.
  • Strong verbal and written communication skills
  • Strong presentation and public speaking skills.

What you can expect of us

As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.

In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.

Apply now and make a lasting impact with the Amgen team.

careers.amgen.com

As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.

We will ensure that individuals with disabilities are provided 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

Junior/L3

L2

L3

L4

L5

L6

Senior/L5

Director

Junior/L3 · Associate Fuel Operations

2개 리포트

$99,200

총 연봉

기본급

$80,652

주식

-

보너스

-

$99,200

$99,200

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