Machine Learning Engineer
The role of the ML Engineer is to help discover information hidden in vast amounts of data and help us make smarter decisions to deliver better products. The primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. The candidate must have strong experience using variety of data mining and data analysis methods, building and implementing models, developing and using algorithms, and running simulations. The candidate must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. This role presents an exciting opportunity to push and deliver market-leading AI based platforms and solutions.
Key Responsibilities
The individual in this role will be responsible for the following:
- Understand business objectives and develop models that help to achieve them, along with metrics to track their progress
- AnalyzeML algorithms available to solve a given problem and select the most appropriate
- Explore and visualize data to gain an understanding, identify differences in data distribution that could affect performance when deploying the model in the real world
- Supervise the data acquisition process. Verify data quality and achieve it via data cleaning
- Find available datasets online that could be used for training
- Define validation strategies
- Define data augmentation pipelines
- Train models and tune their parameters. Analyze errors of the model and design strategies to overcome them
- Deploy models to production
- Provide leadership and coaching to larger engineering team on machine learning techniques
Candidate Profile
The ideal candidate will be a highly articulate technical leader with proven expertise in machine learning/deep learning. Will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field. Will lead all the processes from data collection, cleaning and pre-processing, to training models and deploying them to production.
Essential Skills and Experience
- Degree in computer science, information science, statistics or a related discipline
- 5+ years of programming in large scale production systems, in languages such as Python, Java, Go.
- 3+ years of experience in cloud environments such as AWS/GCP/Azure with experience in cloud services related to ML/DL.
- Extensive data modeling and data architecture skills
- Programming experience in Python, R or Java
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Experience building DL NLP Models for text classification, image analytics-CNN, RNN, LSTM
- Proficiency with machine learning frameworks such as TensorFlow or Keras
- Knowledge of Hadoop or other distributed computing systems
- Experience working in an Agile environment
- Advanced math skills (linear algebra, Bayesian statistics, group theory) are a plus
- Strong written and verbal communication skills