We are looking for a Machine Learning Engineer to work closely with the ML Architect to develop on ML frameworks such as TensorFlow, Scikit-Learn, and Pytorch, as well as an experimentation platform and tools.
The responsibilities of this role include developing large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable.
You will collaborate with cross-functional teams to help deploy and integrate machine learning models.
The position requires liaising with business units for their machine learning needs and working on the cross-business unit machine learning portfolio.
You will optimize feature extraction, transformation, and selection.
The role involves working with and managing feature stores for reusability across machine learning pipelines.
You will ensure the scalability, reliability, cost efficiency, and ease of use of the machine learning platform.
Contributing to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities is also part of the job.
Requirements:
Candidates must have 5+ years of experience as a Machine Learning Engineer.
Strong experience with supervised and unsupervised learning, survival analysis, time series modeling, and statistical forecasting is required.
You should be skilled in building predictive models, such as churn, user journey, and sales forecasting, using behavioral data.
Proficiency with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn is essential.
Experience in model training, versioning, and monitoring is necessary.
A solid background in MLOps practices, including CI/CD, Docker, Kubernetes, Airflow, SageMaker, MLflow, model observability tools, and feature stores, is required.
A business-oriented mindset with the ability to connect model outcomes to product and strategic goals is important.
Benefits:
Flexible working hours are offered to accommodate personal schedules.
Employees can participate in the Mindera Annual Trip, sports, and sharing groups to connect and have fun.
There are opportunities for training and conferences, allowing you to create your own training plan.
You can choose the laptop and peripherals that best suit your needs.
Most importantly, you will work with a great team in a politics-free environment that values commitment, feedback, and empathy.
