Mindera
Computer Software
MachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Machine Learning Engineer at Mindera. Skills: Machine Learning, ML frameworks, predictive models, MLOps practices. Develop large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable. Collaborating with cross-functional teams to help deploy/integrate machine learning models”
What You'll Achieve.
scalability; performance; efficiency; reliability; cost efficiency; ease of use
Industry & Context.
What They're Looking For.
Must Have
5+ years of experience as a Machine Learning Engineer, experience with supervised and unsupervised learning, survival analysis, time series modeling, and statistical forecasting, building predictive models (e. g. churn, user journey, sales forecasting) using behavioral data, ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn, model training, versioning, and monitoring, MLOps practices: CI/CD, Docker, Kubernetes, Airflow, SageMaker, MLflow, model observability tools, and feature stores
Nice to Have
ML Architect collaboration
What You'll Do.
Develop large-scale distributed machine learning systems that are scalable
Collaborating with cross-functional teams to help deploy/integrate machine learning models
Liaise with the BUs for their ML needs and work on the cross-BU ML portfolio
Optimize feature extraction
transformation and selection
Work with and manage Feature Stores for reusability across ML pipelines
and ease of use of the machine learning platform
Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities
How You'll Work.
Team & Collaboration
Collaborating with cross-functional teams; work in a collaborative way; talk to everyone to enhance communication
Communication Scope
talk to everyone to enhance communication
Full Job Description
We are looking for a **ML Engineer ** to work closely with the ML Architect to develop on ML frameworks (TensorFlow, Scikit-Learn, Pytorch), Experimentation platform and tools. This role has the responsabilities to: * Develop large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable * Collaborating with cross-functional teams to help deploy/integrate machine learning models. * Liaise with the BUs for their ML needs and work on the cross-BU ML portfolio. * Optimize feature extraction, transformation and selection. * Work with and manage. * Feature Stores for reusability across ML pipelines. * Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform * Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities **Requirements** * 5+ years of experience as a **Machine Learning Engineer**. * Strong experience with**supervised and unsupervised learning, survival analysis, time series modeling, and statistical forecasting.** * Skilled in **building predictive models (e.g. churn, user journey, sales forecasting) using behavioral data**. * Proficient with **ML frameworks** such as TensorFlow, PyTorch, or Scikit-Learn. * Experienced in **model training, versioning, and monitoring**. * Solid background in MLOps practices: CI/CD, Docker, Kubernetes, Airflow, SageMaker, MLflow, model observability tools, and feature stores. * Business-oriented mindset: ability to connect model outcomes to product and strategic goals **Benefits** ### **The Things We Really Care About:** Most of all you get to work with a bunch of great people, where the whole team owns the project together in a politics-free environment. Our culture reflects our lean and self-organization attitude. We encourage our colleagues to take risks, make decisions, work in a collaborative way and talk to everyone to enhance communication. Freedom and Responsibility go hand in hand, and
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