Engineer III Spec-Data Engineering

1. Deploying machine learning models - On Prem, Cloud and Kubernetes environments
2. Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.
3. Creating and implementing data and ML pipelines for model inference, both in real-time and in batches.
4. Architecting, designing, and implementing large-scale AI/ML systems in a production environment.
5. Monitor the performance of data pipelines and make improvements as necessary

What we’re looking for...

You have strong analytical skills and are eager to work in a collaborative environment with global teams to drive ML applications in business problems, develop end-to-end analytical solutions, and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and can interact with various partners and multi-functional teams to implement data science-driven business solutions.

You'll need to have:

1. Bachelor's degree with four or more years of relevant work experience.
2. Expertise in advanced analytics/ predictive modelling in a consulting role.
3. Experience with all phases of end-to-end Analytics project
4. Hands-on programming expertise in Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) , R (for specific data analysis tasks)
5. Knowledge of Machine Learning Algorithms - Linear Regression , Logistic Regression ,Decision Trees ,Random Forests ,Support Vector Machines (SVMs) ,Neural Networks (Deep Learning) ,Bayesian Networks
6. Data Engineering - Data Cleaning and Preprocessing ,Feature Engineering ,Data Transformation , Data Visualization
7. Cloud Platforms - AWS SageMaker ,Azure Machine Learning ,Cloud AI Platform

Even better if you have one or more of the following:

1. Advanced degree in Computer Science, Data Science, Machine Learning, or a related field.
2. Knowledge on Home domain with key areas like Smart Home, Digital security and wellbeing
3. Experience with stream-processing systems: Spark-Streaming, Storm etc.