Product Machine Learning Engineer

Product Machine Learning Engineer

Argentina

Operations /

Remote Full Time /

Remote

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🚀 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 Product Machine Learning Engineer to help take our expertise —and our internal optimization platform— to the next level. If you consider yourself a data nerd like us, we’d love to connect!

As a key contributor, you'll play a pivotal role in designing, deploying, and maintaining ML models that power our product for marketing campaign budget optimization and allocation. You’ll work closely with the product team and business stakeholders, bringing robust systems into production, introducing fresh technical insights, and ensuring our models deliver real business impact.

If you thrive on building scalable ML pipelines, solving complex challenges, and shaping products that drive decision-making at scale, we’re eager to connect with you! 🐶🚀

🚀 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 🤓

• Design, build, and maintain robust data pipelines and ML workflows for training and inference.
• Develop, test, and deploy machine learning models into production environments.
• Model Development: research, train, evaluate, and tune ML Models ensuring scalability, robustness, and integration using MLOps best practices (model versioning, CI/CD, automated retraining) and applying Statistical Analysis techniques.
• Monitoring & Maintenance: Track model performance, detect drift, retrain, and update/optimize them.
• Create ML Proof of Concepts (POCs) to validate, enhance, and refine already implemented solutions.
• Research and implement emerging ML/AI techniques to enhance solutions.
• Work with data scientists, data engineers, and product managers to align ML solutions with business needs.
• Write clear documentation, enforce best practices in code, testing, and reproducibility.

Required Skills

• Solid understanding of machine learning fundamentals (supervised, unsupervised, evaluation metrics, overfitting, etc.).
• Experience with feature engineering and model fine-tunning.
• Model tracking/versioning/monitoring (MLflow, Airflow, Grafana or similar).
• Cloud platforms (AWS) and containerization (Docker).
• Experience deploying ML-based systems to production, including full model lifecycle management, monitoring, and MLOps pipeline setup.
• Strong Python skills (NumPy, SciPy, Pandas, Plotly, XGBoost, Statsmodels).
• SQL proficiency; familiarity with relational database management systems (Postgres).

Nice to Have Skills 😉

• Experience using Bayesian modeling libraries (through PyMC/Bambi or similar).
• Experience in the Marketing Tech ecosystem (Google Ads/Meta Ads or similar)
• Experience working in the development and integration of machine learning solutions into a SaaS Product (software as a service).
• Detect model impact in the clients' business beyond _lab_metrics
• Work with product non-tech stakeholders to interpret how we can solve business problems with ML/AI
• Experience on Model Serving (REST APIs, FastAPI, Kubernetes).
• Experience building ETL/ELT pipelines.
• Research Exposure**:** Reading and adapting academic papers into production & Contributing to open-source ML projects.
• Experience building and maintaining automated data ingestion, training, and deployment pipelines

🎁 Perks

• 🌍 Remote-first culture – work from anywhere!
• 🚀 In-Company English Lessons.
• 💪 Wellhub or sports club stipend to stay active
• 🚀 AWS & Databricks certifications fully covered (reward salary increase for AWS certifications!)
• 🍕 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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