Mindera
Computer Software
MachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Machine Learning Engineer at Mindera. Skills: Machine Learning Engineer, TensorFlow, Scikit-Learn, Pytorch, supervised and unsupervised learning, time series modeling, statistical forecasting, predictive models, model training, model versioning, model monitoring, MLOps practices, Docker, Kubernetes, Airflow, SageMaker, MLflow. Develop large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable. Collaborating with cross-functional teams to help deploy/i”
What You'll Achieve.
connect model outcomes to product and strategic goals
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, Business-oriented mindset: ability to connect model outcomes to product and strategic goals
Nice to Have
ML Architect, Experimentation platform and tools, scalable, performant, efficient, and reliable machine learning systems, deploy/integrate machine learning models, cross-BU ML portfolio, Feature Stores for reusability across ML pipelines, scalability, reliability, cost efficiency, and ease of use of the machine learning platform, evaluating and adopting new technologies and tools to enhance our machine-learning capabilities
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; the whole team owns the project together
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:** * Health Insurance, because health comes first * Flexible working hours * Open holidays, take the time you need for yourself * Profit distribution for everyone * Mindera Annual Trip, Sports, and sharing groups to connect and have fun! * Training & conferences, create your own training plan * Child Care vouchers **Other good things:** * Choose Laptop & Peripherals that best suit
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