Mutt Data
Machine Learning Engineer
Remote Machine Learning Engineering role with clear candidate location fit.
PostedJul 4, 2026
Eligible countries1 accepted country
Seniority signalMiddle
Work settingRemote
Accepted candidate locations
Argentina
Role overview
Machine Learning Engineer
Requirements and responsibilities
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🚀 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
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!
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