Career Category
Engineering
Job Description
ABOUT THE ROLE
You will play a key role in a regulatory submission content automation initiative which will modernize and digitize the regulatory submission process, positioning Amgen as a leader in regulatory innovation. The initiative leverages state-of-the-art technologies, including Generative AI, Structured Content Management, and integrated data to automate the creation, review, and approval of regulatory content.
Role Description:
We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background and experience working with Large Language Models (LLMs) to join our team. You will play a pivotal role in building and scaling our machine learning models and LLM applications from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable pipelines and applications.
Roles & Responsibilities:
Develop and deploy applications that utilize LLMs such as OpenAI GPT 4, Claude, Gemini
Build and maintain MLOps pipelines, including data ingestion, versioning, chunking, vectorization, feature engineering, model training, deployment, and monitoring.
Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
Implement DevOps/MLOps/LLMOps best practices 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
Functional Skills:
Must-Have Skills:
Strong foundation in machine learning algorithms and techniques
Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, langchain)
Familiar with AWS, Azure, or Google Cloud;
Good-to-Have Skills:
Experience in building custom solutions using LLMs to meet specific business needs
Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
Experience with data engineering and pipeline development
Soft Skills:
Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented, with a focus on achieving team goals
Strong presentation and public speaking skills.
Basic Qualifications:
Master’s degree and 1-3 years of experience in Software Engineering, Data Science or Machine Learning Engineering preferred OR
Bachelor’s degree and 3 to 5 years of Software Engineering, Data Science or Machine Learning Engineering OR
Diploma and 7 to 9 years of I Software Engineering, Data Science or Machine Learning Engineering experience
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 an accommodation.
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