Machine Learning Engineer

2 days ago

Hyderabad, Telangana, India Amgen Inc Full time ₹ 8,00,000 - ₹ 24,00,000 per year

*What you will do*

In this vital role We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.

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, GCP, Azure) for ML model development, training, and deployment.
  • Implement DevOps/MLOps 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

Basic Qualifications:

  • Master's degree / Bachelor's degree and 5 to 9 years [Job Codes Discipline and/or Sub-Discipline]

Functional Skills:

Must-Have Skills:

  • 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., TensorFlow, PyTorch, Scikit-learn)
  • Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and interpersonal 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

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