3 days ago
Hyderābād, IndiaSenior / Staff+
Responsibilities
- Design, develop, train, evaluate, deploy, and maintain predictive machine learning models across forecasting, classification, regression, anomaly detection, clustering, and recommendation use cases.
- Perform data exploration, preprocessing, feature engineering, feature selection, model experimentation, hyperparameter tuning, cross-validation, backtesting, and error analysis.
- Build reusable ML pipelines for data ingestion, training, validation, deployment, monitoring, retraining, model versioning, and reproducible workflows.
- Develop and operate production APIs, services, and machine learning workloads primarily on AWS.
- Implement model monitoring and alerting for accuracy, forecast performance, data quality, drift, bias, latency, reliability, and infrastructure performance.
- Conduct A/B testing and experimentation and troubleshoot model, data, pipeline, application, and production-environment issues.
- Develop Generative AI and LLM applications using document processing, chunking, embeddings, vector search, prompt engineering, RAG, evaluation, and monitoring.
- Implement security, privacy, access control, governance, explainability, responsible AI, documentation, and deployment standards.
- Collaborate with data scientists, data engineers, software engineers, DevOps teams, product teams, and business stakeholders.
- Participate in technical design, code reviews, sprint planning, backlog refinement, estimation, and occasional off-hours production support.
Requirements
- Bachelor’s or master’s degree in Software Engineering, Data Science, Machine Learning Engineering, Computer Science, Information Technology, or a related field, plus 5–8 years of relevant experience.
- Strong hands-on experience with Python, SQL, machine learning algorithms, predictive modeling, statistical methods, model evaluation, feature engineering, model training, and forecasting.
- Experience developing and deploying production machine learning models and implementing MLOps pipelines for deployment, monitoring, versioning, and retraining.
- Experience with machine learning libraries such as Scikit-learn, PyTorch, TensorFlow, or XGBoost.
- Experience with AWS cloud-based machine learning development and deployment, including services such as SageMaker, S3, Lambda, ECR, ECS, EKS, Step Functions, and CloudWatch.
- Experience building APIs or services for machine learning models and using Git, CI/CD, automated testing, Docker, and software engineering best practices.
- Understanding of model monitoring, data drift, concept drift, bias, explainability, model-performance degradation, responsible AI, and governance.
- Preferred experience includes advanced time-series forecasting, NLP, computer vision, recommendation systems, optimization, feature stores, distributed training, model serving, data engineering, ETL/ELT, Spark, and regulated industries.
- Preferred experience includes MLflow, Databricks Machine Learning, Azure Machine Learning, Vertex AI, Kubernetes, infrastructure as code, AWS-native MLOps, and cloud-native deployment patterns.
- Preferred experience includes LLM applications using OpenAI GPT, Claude, Gemini, Amazon Bedrock models, RAG, embeddings, vector databases, LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
- Preferred certifications include AWS Machine Learning Engineer, AWS Solutions Architect, Databricks Machine Learning, Microsoft Azure AI/Data Scientist, Google Cloud Professional Machine Learning Engineer, DevOps, Kubernetes, data engineering, or AI certifications.
- Strong analytical, debugging, troubleshooting, communication, presentation, collaboration, ownership, prioritization, and stakeholder-explanation skills.
Tech Stack
Categories
About Amgen
Amgen is a public biotechnology company that discovers, develops, manufactures, and sells biologic and biosimilar therapeutics for patients with serious diseases. Its portfolio and pipeline span oncology, cardiovascular disease, osteoporosis, inflammation, and rare diseases, marketed globally through direct sales and partnerships. Founded in 1980 and headquartered in Thousand Oaks, California (NASDAQ: AMGN), Amgen is a component of the Dow Jones Industrial Average and completed the acquisition of Horizon Therapeutics in 2023.