The ideal candidate must have the following qualifications: 4 + years experience in practical implementation and deployment of large customer-facing ML based systems.
In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
Programming skills in Python is a must
Experience in developing and deploying on cloud (AWS or Google or Azure)
Good verbal and written communication skills
Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow
Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.
Roles and Responsibilities
Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy, efficacy, and robustness
Suggest innovative and creative concepts and ideas that would improve the overall platform
Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.
Mentor and coach other team members
Evaluate the performance of NLP models and ideate on how they can be improved
Support internal and external NLP-facing APIs
Keep up to date on current research around NLP, Machine Learning and Deep Learning