Machine Learning Engineer

hace 2 semanas

Mexico City SelektIT A tiempo completo

Job Description:

A machine learning engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle of a product that our users love. ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. The role may also involve performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design
Key Skills : 

Python, GCP, Vertex AI or Tensor Flow, DS, Building & Scale Models, leverage GenAI models

Qualifications:

  • 4 + years of relevant work experience.
  • Experience with modern scripting languages (Python).
  • Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc.
  • Experience in modern web application frameworks such as Node.js.
  • Experience in writing SQL queries against a relational database.
  • Experience in version control systems (preferably Git).
  • Experience in Google Cloud Platform and AI/ML-related components such as Vertex AI, BigQueryML, and AutoML.
  • Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.
  • Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embedding generation and utilization.
  • Experience in training machine learning models with extremely large datasets.
  • Experience in front-end technology and frameworks like HTML, CCS, JavaScript, ReactJS, and D3.
  • Experience in REST and effective web service design.
  • Experience in production systems design including High Availability.
  • Disaster Recovery, Performance, Efficiency, and Security.
  • Experience in cloud computing platforms and associated automation patterns and machine learning services they provide.
  • Experience in defensive coding practices and patterns for high-availability

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