Job Description
Looking for an AI Architect with 9 to 12 yrs of experience in Data Sciences as a Data Scientist and Architect to build and deploy the Advanced Digital Solutions on Cloud Platform. Ideal candidate must have hands-on development experience in Python, and Web Services, to build and deploy AI applications using Machine Learning, NLP and Deep Learning algorithms. Should be able to understand the problem statement, Data and build the most optimal solution to address the problem statement.
Roles & Responsibilities
- Architecture design, total solution design from requirements analysis, design and engineering for data ingestion, pipeline, data preparation & orchestration, applying the right ML algorithms on the data stream and predictions.
- Hands-on programming and architecture capabilities in Python, R, or SCALA
- Responsible for designing and architecting the Solutions using AI and Machine learning technology.
- Should have working knowledge and expertise in building Enterprise wide Generative AI applications using LLM's, SLM's.
- Translation of business needs into a conceptual and technical architecture designs of AI models and build solutions
- Collaborate with business partners and clients for AI solutioning and use cases. Provide recommendations to drive alignment with business teams
- Define and implement evaluation strategies for each model, demonstrate applicability and performance of the model, and identify its limits
- Review the code by the team and the Partner resources, and suggest the optimal techniques to optimize the code
- Design complex system integrations of AI technologies with API-driven platforms, using best practices for security and performance
- Experience in languages, tools & technologies such as Python, Tensorflow, Pytorch, Kubernetes, Docker, etc
- Experience with MLOps tools (like TFx, Tensorflow Serving, KubeFlow, etc.) and methodologies for CI/CD of ML models
- Follow DevOps methodology and PEP standards to build the AI Solutions.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Defining, designing and delivering ML architecture patterns operable in native and hybrid cloud architectures.
- Perform research activities to identify emerging technologies and trends that may affect the Data Science/ ML life-cycle management in enterprise application portfolio.
- Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.
Technical Skills
Must have Skills & Experience
- Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)
- In depth knowledge and expertise in building the NLP based solutions using the Advanced NLP techniques such as Attention based transformers, etc
- Hands-on expertise in building Deep Learning techniques using Neural Networks (ANN, CNN, RNN, LSTM, etc)
- Experience in building Python Microservices
- Expertise in building the webservices using Flask, Django frameworks
- Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.)
- Hands-on experience in following DevOps methodologies and Agile framework
Good To Have Skills
- Hands on experience in RDBMS, NoSQL, big data stores like: Elastic, Cassandra, Hbase, Hive, HDFS Work experience as Solution Architect/Software Architect/Technical Lead roles
- Experience with open source software.
- Excellent problem-solving skills and ability to break down complexity.
- Ability to see multiple solutions to problems and choose the right one for the situation. Excellent written and oral communication skills.
- Experience in building the Cloud native and Cloud deployable solutions on Azure, AWS.
