Associate Machine Learning Engineer

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:   The   Associate Machine Learning Engineer   position offers a unique opportunity to join a fun, innovative engineering team within the   AI & Data Science   (AI&D)   organization.   You’ll   work on next-generation capabilities and services in   Applied   AI   & Automation   using innovative   COTS products,   open-source software, frameworks, tools, and cloud computing services. The role also emphasizes   demonstrating   these capabilities to support critical business operations and initiatives,   in ensuring quality, compliance, and performance across Amgen’s   Applied AI &   Automation Footprint.   The   role   is responsible for   building and scaling our   AI and   machines   learning   solutions   from development to production. Your   expertise   in   MLOps   will be essential in creating efficient and reliable ML pipelines.   The role   represents   working in   the solution engineering and DevOps teams to lead the transition from Intelligent automation to Agentic Process Automation and   ensure s   that strategy and implementation remain connected throughout the value stream.   The ideal candidate has experience in   building AI & ML solutions ,   has   excellent communication skills, and a n   understanding of   Agile methodologies .   This role focuses on supporting the development, deployment, operation, and reliability of AI and   LLM ‑ based   solutions in production environments, working under guidance of senior engineers and platform teams. The position emphasizes operational excellence, observability, and compliance for applied AI and GenAI systems.     Roles & Responsibilities:     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,   Databricks ) for ML model development, training, and deployment.   Develop solutions using   DevSecOps   framework   that   are secure, scalable, reliable, and aligned with enterprise architecture standards.   Evaluate model performance using   appropriate metrics   and   optimize   models for accuracy and efficiency   Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software   Create and   maintain   documentation on software architecture, design, deployment, disaster recovery, and operations   Identify   and resolve technical challenges effectively   Provide ongoing support and maintenance for applications, ensuring   that   they   operate   smoothly and efficiently   Analyze customer feedback and support data to   identify   pain points and opportunities for improvement   Evaluate and recommend technologies and tools that best fit the solution requir ements   Support operationalization of machine learning and GenAI models developed by data scientists and solution teams.   Assist   in evaluating model and LLM performance using metrics related to reliability, efficiency, and response quality.   Support deployment and operation of   LLM ‑ based   workflows, including prompt configurations,   retrieval ‑ augmented   generation (RAG) pipelines, and   agent ‑ based   automations.   Assist   with monitoring AI and LLM systems for availability, latency, error rates, and quality degradation.   Support model, prompt, and pipeline versioning across development, test, and production environments.   Participate in incident triaging, root cause analysis, and rollback or mitigation activities for AI services.   Assist   with evaluation runs for LLM outputs, including grounding, reliability, and safety checks.   Follow established AI governance, security, and compliance standards when   operating   AI and GenAI solutions.   Monitor AI and LLM endpoints for availability, latency, throughput, and error rates using enterprise monitoring tools.   Assist   with dashboards, alerts, runbooks, and operational documentation to support reliable AI system operations.     Basic Qualifications and Experience:   [GCF Level 3]   Any degree and 2 to 6 years of Computer Science,   IT   or related field experience Functional Skills:   Must-Have Skills :   Strong foundations in machine learning algorithms and techniques   Experience in   MLOps   practices and tools (e.g.,   MLflow , Kubeflow, Airflow); Experience in model monitoring, including model observability and explainability   Proficiency   in Python (or R) and relevant ML libraries (e.g., TensorFlow,   PyTorch , Scikit-learn)   Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing   Understanding of the LLM inference lifecycle, including prompt execution, retrieval, and response generation.   Awareness of common LLM failure modes such as hallucinations, prompt injection, and data leakage.     Good-to-Have Skills:   Good   understanding of cloud platforms (e.g., AWS,   Databricks ) and containerization technologies (e.g., Docker, Kubernetes)   Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)    Experience with data processing tools like Hadoop, Spark, or similar   K nowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering   DSLs   and agent frameworks (e.g.,   LangChain , Semantic Kernel).   Ability to analyze client requirements and translate them into solutions   Exposure to LLM evaluation techniques beyond accuracy, including grounding, faithfulness, latency, and   reliability of   metrics.   Soft Skills:   Excellent   critical-thinking and   problem-solving skills    Strong communication   and collaboration skills   Demonstrated awareness of how to function in a team setting   Demonstrated awareness of presentation skills       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.   .