Senior Machine Learning Engineer – Recommendation Systems
🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Muttdata 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! 🐶🚀
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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
🔍 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 production recommendation systems at consumer scale.
Develop ranking and retrieval models to improve personalization and user experience.
Own ML pipelines end-to-end, from feature engineering and training to deployment and monitoring.
Collaborate with client stakeholders and engineering teams to deliver scalable ML solutions.
Analyze large-scale user behavior data and run A/B tests to optimize recommendation performance.
Improve reliability, scalability, and latency of production ML systems on AWS/GCP/Azure.
Required Skills
6 years of experience in Software/Data Engineering or ML roles.
4+ years building and operating ML systems in production.
2-3+ years working on recommendation systems, ranking, retrieval, or personalization.
Strong Python and SQL skills. Experience with PyTorch or TensorFlow.
Experience deploying ML systems on AWS, GCP, or Azure.
Experience working with large-scale consumer data and production environments.
Advanced English level and ability to work autonomously with stakeholders.
Experience in e-commerce, adtech, martech, or consumer products.
Experience with A/B testing, feature stores, Spark, or low-latency inference systems.
🎁 Perks
Remote-first culture – work from anywhere! 🌍
AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
In-Company English Lessons.
Birthday off + an extra vacation week (Mutt Week! 🏖️)
Referral bonuses – help us grow the team & get rewarded!
Maslow: Monthly credits to spend in our benefits marketplace.
✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
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Apply To This Job
Muttdata 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! 🐶🚀
\n
🚀 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 production recommendation systems at consumer scale.
Develop ranking and retrieval models to improve personalization and user experience.
Own ML pipelines end-to-end, from feature engineering and training to deployment and monitoring.
Collaborate with client stakeholders and engineering teams to deliver scalable ML solutions.
Analyze large-scale user behavior data and run A/B tests to optimize recommendation performance.
Improve reliability, scalability, and latency of production ML systems on AWS/GCP/Azure.
Required Skills
6 years of experience in Software/Data Engineering or ML roles.
4+ years building and operating ML systems in production.
2-3+ years working on recommendation systems, ranking, retrieval, or personalization.
Strong Python and SQL skills. Experience with PyTorch or TensorFlow.
Experience deploying ML systems on AWS, GCP, or Azure.
Experience working with large-scale consumer data and production environments.
Advanced English level and ability to work autonomously with stakeholders.
Experience in e-commerce, adtech, martech, or consumer products.
Experience with A/B testing, feature stores, Spark, or low-latency inference systems.
🎁 Perks
Remote-first culture – work from anywhere! 🌍
AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
In-Company English Lessons.
Birthday off + an extra vacation week (Mutt Week! 🏖️)
Referral bonuses – help us grow the team & get rewarded!
Maslow: Monthly credits to spend in our benefits marketplace.
✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
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Apply To This Job