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Muttdata

Posted 4 months ago

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Machine Learning Engineer

ArgentinaRemoteFull-time

AI Summary

A Machine Learning Engineer designs, builds, and optimizes scalable ML models and MLOps pipelines for demand planning, forecasting, and recommendation systems, collaborating with stakeholders to deliver data-driven solutions.

About this role

🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀

Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.

We’re looking for a Machine Learning Engineer to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀

🚀 What We Do

  • Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
  • Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
  • Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
  • Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
  • Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
  • Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

    • 🌟 Our Partnerships

  • Amazon Web Services
  • Astronomer
  • Databricks

    • 🌟 Our Values

  • 📊 We are Data Nerds
  • 🤗 We are Open Team Players
  • 🚀 We Take Ownership
  • 🌟 We Have a Positive Mindset

    • 🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀

    Responsibilities 🤓

  • Develop and optimize ML models, ensuring scalability, monitoring, and integration with MLOps best practices.
  • Implement client requirements, from exploratory data analysis (EDA) to feature engineering and model lifecycle management.
  • Build ML Proof of Concepts (POCs) to validate and refine solutions.
  • Optimize models for performance, latency, memory, and throughput.
  • Apply statistical analysis techniques and develop regression models.
  • Design and maintain feature stores and data pipelines for ML workflows.
  • Research and implement emerging ML/AI techniques to enhance solutions.
  • Collaborate with stakeholders to align technical solutions with business needs.

    • Required Skills

  • Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.
  • Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly).Knowledge of SQL
  • Experience with cloud platforms (AWS, GCP, Azure).

    • Nice to Have Skills 😉

  • Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks, or similar).
  • Background in modern LLM technologies.
  • Understanding of Deep Learning frameworks (Keras, PyTorch, TensorFlow).Basic knowledge of Docker.

    • 🎁 Perks

  • 🌍 Remote-first culture – work from anywhere!
  • 🚀 In-Company English Lessons.
  • 💪 Wellhub or sports club stipend to stay active
  • 🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
  • 🍕 Food credits via Pedidos Ya – because great work deserves great food.
  • 🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)
  • 🤝 Referral bonuses – help us grow the team & get rewarded!
  • ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!

    • Skills

    AirflowAWSAzureDatabricksDockerGCPJupyterKerasMLflowMLOpsNumPyPandasPythonPyTorchSciKit-LearnSQLTensorFlowXGBoost

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