MACHINE LEARNING ENGINEER
Descrição da oferta de emprego
The role is part of the client's ML Platform team, focusing on scaling ML capabilities to meet team and company goals.
Key responsibilities include designing and implementing infrastructure and tools for developing and deploying machine learning models, both batch and real-time, using cutting-edge technology on the Snowflake platform.
The position involves migrating to the Snowflake platform along with other modern data stack tools such as AWS (Sagemaker).
What will you do? Contribute to the design, development, and deployment of the ML platform Define and implement best practices for training, evaluating, and deploying machine learning models at scale Collaborate with software engineers, data engineers, and data scientists on end-to-end ML solutions Extend and maintain a self-service platform for data science teams What are we looking for? Educational background in Computer Science Hands-on experience in machine learning engineering, with a track record of designing and deploying large-scale ML systems Extensive knowledge of software development with Python and SOLID principles Vast experience with SQL Understanding of machine learning techniques and MLOps Solid experience with Snowflake Knowledge of Infrastructure as Code (Terraform or similar) Practical knowledge of AWS, GCP, or Azure Experience with cloud technologies like Vertex, Dataflow, Cloud Run, BigQuery, Datastore, Cloud Storage, Cloud Functions, and PubSub Experience with Snowflake Cortex / AWS Bedrock, AWS MSK, Snowpipe Streaming What can you expect from us? A permanent job contract for a long term project Tech equipment + SIM Card + personal smartphone Health and Life Insurance Social events and team buildings The commitment of letting you grow with us, and be rewarded accordingly A dynamic and young team that will be always there to support you Formation in the latest technologies Coffee, fruits, snacks and a warm welcoming when you pass by the office
Detalhes da oferta
- Caixa Mágica Software
- Indeterminado
- 18/09/2024
- 17/12/2024
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