Machine Learning Engineer

Team: Operations

Location: Argentina

Commitment: Remote Full Time

Workplace Type: remote

🚀 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!