About
Collaborate closely with data scientists, engineers, and stakeholders to turn ideas into impactful solutions.
Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT.
Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines.
Work with large-scale data using PySpark and integrate ML solutions into production environments.
Monitor and improve model performance to ensure accuracy and efficiency.
Contribute to team knowledge by mentoring and supporting colleagues.
Bring creativity and fresh perspectives to problem-solving and technical solutions.
What Were Looking For: We welcome applications from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch).
Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe).
Experience with ML lifecycle tools (MLflow, Kubeflow, Azure ML Pipelines).
Knowledge of distributed data processing (PySpark) and software engineering principles (Git).
A collaborative mindset and excellent problem-solving abilities.
Experience in data cleansing, exploratory data analysis, and visualisation.
A continuous learning mindset and interest in emerging AI/ML technologies.
Why Join Us? Work on impactful AI projects with real-world applications.
Be part of a collaborative and forward-thinking team.
Access to continuous learning and development opportunities.
Flexible working arrangements and a supportive work culture.
TPBN1_UKTJ
Languages
- English
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