Role – Deep Learning Engineer & Data Scientist
Please read the information in this job post thoroughly to understand exactly what is expected of potential candidates.
Job Description :
- Be a hands-on problem solver with a consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges.
Use the knowledge of a wide variety of AI / ML techniques and algorithms to find what combinations of these techniques can best solve the problem.
Improve Model accuracy to deliver greater business impact.Estimate business impact due to deployment of the model.Work with the domain / customer teams to understand business context, data dictionaries, and apply relevant Deep Learning solutions for the given business challenge.Work with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines.Design, develop & deploy Deep Learning models using Tensorflow / Pytorch.Experience in using Deep Learning models with text, speech, image, and video data.Design & develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, and Semantic Search using NLP tools like Spacy and open-source Tensorflow, Pytorch, etc.
Design and develop Image recognition & video analysis models using Deep Learning algorithms and open-source tools like OpenCV.Knowledge of state-of-the-art Deep Learning algorithms.Optimize and tune Deep Learning models for the best possible accuracy.Use visualization tools / modules to explore and analyze outcomes & for Model validation (e.g., using Power BI / Tableau).Work with application teams in deploying models on cloud as a service or on-prem.Deployment of models in Test / Control framework for tracking.
Build CI / CD pipelines for ML model deployment.Integrate AI & ML models with other applications using REST APIs and other connector technologies.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.Technology / Subject Matter Expertise :
Sufficient expertise in machine learning, mathematical and statistical sciences.Use of versioning & collaborative tools like Git / Github.Good understanding of the landscape of AI solutions – cloud, GPU-based compute, data security and privacy, API gateways, microservices-based architecture, big data ingestion, storage and processing, CUDA Programming.Develop prototype-level ideas into a solution that can scale to industrial-grade strength.Ability to quantify & estimate the impact of ML models.Soft Skills Profile :
Curiosity to think in fresh and unique ways with the intent of breaking new ground.Must have the ability to share, explain and “sell” their thoughts, processes, ideas, and opinions, even outside their own span of control.Ability to think ahead and anticipate the needs for solving the problem will be important.Ability to communicate key messages effectively and articulate strong opinions in large forums.Desirable Experience :
Keen contributor to open source communities, and communities like Kaggle.Ability to process huge amounts of data using Pyspark / Hadoop.Development & application of Reinforcement Learning.Knowledge of Optimization / Genetic Algorithms.Operationalizing Deep Learning models for a customer and understanding nuances of scaling such models in real scenarios.Understanding of stream data processing, RPA, edge computing, AR / VR, etc.Appreciation of digital ethics, data privacy will be important.Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus.Experience in platforms like Data Robot, Cognitive Scale, H2O.AI etc. will all be a big plus.J-18808-Ljbffr
