Machine Learning Engineer
hace 1 mes
At Intelygenz, we envision a future where processes accelerate performance. For the companies we work with, this means finding ways to optimize their data using cutting-edge technologies like AI-enabled automation. This mindset is a huge part of our culture. We thrive on pooling our skills, collaborating on projects, helping one another learn and creating innovations.
What are you going to do?
- As a Machine Learning Engineer, your responsibilities will be:
- Designing and implementing end-to-end inference pipelines.
- Designing and implementing ETL pipelines for AI solutions deployed on production environments.
- Designing and implementing Feedback Loop for AI solutions deployed on production environments.
- Fine-tuning of ML and DL models for production purposes.
What will make you succeed in your role?
- Wide experience working with GIT.
- Minimum experience in deploying and maintaining ML models in production.
- Minimum experience in working with Docker and/or Kubernetes.
- Minimum experience working with different database types such as SQL, Document-oriented, Key-Value, and Time Series.
- Minimum experience working with some event brokers such as Kafka, RabbitMQ, NATS...
- Experience working with API frameworks.
- Minimum experience working with Protobuf.
- Data Architectures designed for exploiting and using Machine Learning techniques.
- Modeling fine-tune for ML and DL algorithms.
- Minimum experience using Python 3.8+ and PyTorch.
- Some experience with GoLang.
- High control of the different steps regarding the ML experiments to execute.
- Fluent in English for day-to-day, customer meetings and reporting.
- Strong self-taught and proactivity capabilities.
- Problem-solving and autonomy when facing new challenges.
Bonus Points:
- Experience working with Kubernetes.
- Experience working with Graph databases.
- Comfortable with TDD/ATDD.
- Comfortable with fully automated CI/CD environments.
- Other programming languages: Node.js, C/C++ or Java.
- Desire to learn & constant curiosity.
- Ability to adapt to different environments and projects.
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