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Machine Learning Engineer Senior

Role overview

Qualifications

  • 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)
  • Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks, or similar)

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.

About the company

MUTT DATA logo

MUTT DATA

Artificial Intelligence & Machine Learning Services

Mutt Data is a technology company that helps startups and big companies build and implement Machine Learning solutions that drive real business results. Whether you work in finance, insurance, advertising, telcos, on-demand services or e-commerce, our solutions will help you get ahead of your competition with the latest technologies, techniques and best practices We Are Astronomer & Amazon Consulting Partners. We Are #DataNerds.

Company details

Company typeScaleup
IndustryArtificial Intelligence & Machine Learning Services
Company size51 - 200

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Job description

πŸš€ Join Our Data Products and Machine Learning Development Remote Startup! πŸš€
 
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! πŸΆπŸš€

πŸš€ 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
  • πŸ“Š We are Data Nerds
  • πŸ€— We are Open Team Players
  • πŸš€ We Take Ownership
  • 🌟 We Have a Positive Mindset
  •  
    πŸ” 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! πŸš€

    Responsibilities πŸ€“
  • 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 πŸ˜‰
  • 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!
  • πŸš€ In-Company English Lessons.
  • πŸ’ͺ Wellhub or sports club stipend to stay active
  • πŸš€ AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
  • πŸ• Food credits via Pedidos Ya – because great work deserves great food.
  • πŸŽ‚ Birthday off + an extra vacation week (Mutt Week! πŸ–οΈ)
  • 🀝 Referral bonuses – help us grow the team & get rewarded!
  • ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
  • Apply once. Then go straight to the hiring manager.

    After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

    MR

    Marcus Rivera

    Chief Revenue Officer

    m.rivera@company.com
    linkedin.com/in/marcusrivera
    Unlocked after you apply
    Β·

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