Senior Manager - AI/ML Solution Designer - DTH Industry

Responsibilities -

- Deliver scalable, low latency, and high-performance AI/ ML solutions for DTH

- Build AI/ML pipelines end-to-end, including stages such as data pre-processing, model generation, cross-validation, and efficient systems for processing large amounts of data; be proficient with distributed programming frameworks such as Hadoop/Spark

- Drive solutions by leveraging different open-source libraries and distributed systems

- Work closely with Data Scientists and generate scalable system and model architectures for enabling real-time ML/AI services. Liaise with architects and engineers from other product teams to build solutions and drive (ADOPTION/ADAPTATION)

- Required to assess Business Problems Technical problems and come up with best fit solution and architecture

- Propose techniques frameworks and algorithms and provide technology consultation and assisting and defining the solution develop the solution and deployment of the solution using the next generation technologies like Machine Learning, Deep Learning, NLP and Artificial Intelligence

- Strong Experience in building real world AI ML systems and Productizing and Scaling them in a large scale distributed model and system integration experience. Prior solutioning experience with No SQL databases data streaming and integrating unstructured data. Experience in Large Scale Digital architectures real time systems will be desired. Experience in building robust data pipelines and familiarity with ETL Data Wrangling tools

- Hands-on programming experience in JVM languages and Python

- Familiarity with Machine Learning algorithms. Ability to design ML systems end-to-end this includes big data handling, pre-processing, model generation logic, model persistence including choice of online data stores, etc., systems for consuming active feedback (online learning), and web services to publish model predictions to consumers

- Good overview of warehouse technologies such as Redshift, Informatica and reporting tools such as business objects and Tableau.

- Study and transform data science prototypes

- Research and review appropriate ML algorithms and tools

- Should be aware of tools such as AWS sage maker, Azure machine learning, ONNX other AI services such as polly, forecast, lex, recommendation etc

- Evaluate and finalize machine learning applications according to requirements

- Run machine learning tests and experiments

- Perform statistical analysis and fine-tuning using test results

- Keep abreast of developments in the field

- Proven experience as a Machine Learning Engineer or similar role

- Understanding of data structures, data modeling and software architecture

- Deep knowledge of math, probability, statistics and algorithms

- Ability to write robust code in Python, Java and R

- Familiarity with machine learning frameworks (like Keras or PyTorch, Swift AI, Tensorflow, SAS, Deeplearning4j) and libraries (like scikit-learn)