Machine Learning Engineer

hace 1 semana


Madrid, Madrid, España Amazon A tiempo completo

About the Role

We are seeking a highly skilled Machine Learning Engineer to join our team at Amazon. As an Applied Scientist, you will play a key role in shaping the vision and roadmap of science-based solutions from beginning to end.

Your Key Responsibilities:

  • You will contribute to building and maintaining an MLOps Platform that supports end-to-end scientific operations for a wide range of AI/ML use cases.
  • You will be responsible for the seamless integration of scientific products with existing systems, leading to increased operational efficiency and productivity across OTS.
  • You will also have the opportunity to leverage our foundational GenAI platform to help OTS customers build GenAI applications for their use cases.

About You

To be successful in this role, you should have a strong background in machine learning, including supervised and unsupervised learning algorithms. You should also have experience developing, building, and implementing complex software systems, especially involving ML, that have been successfully delivered to customers.

Apart from technical skills, you should be able to communicate effectively both written and verbally. You should also have experience working with big data technologies (e.g., Hadoop, Spark) and knowledge of RAG and its applications.

What We Offer

As an employee at Amazon, you can expect a competitive salary of $$141,000 per annum, plus additional benefits such as Medical, Dental, and Vision Coverage, Maternity and Parental Leave Options, Paid Time Off (PTO), 401(k) Plan, and many more.

Additional Requirements

  • MS or PhD in quantitative field (CS, CE, ML preferred) or equivalent relevant work experience.
  • Experience with fine-tuning and deploying Large Language Models (LLMs) for customer-facing GenAI applications.
  • Experience with Infrastructure as Code (IaC) and AWS Cloud Development Kit (CDK).
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, Airflow).
  • Experience with MLOps tools and frameworks (e.g., SageMaker, MLflow).
  • Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain).

Contact Information

Please submit your resume and a cover letter explaining why you are suitable for this position.



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