AIML Lead

JOB DESCRIPTION:

The ideal candidate is expected to show strong business acumen and understand business problems,
develop hypotheses and test the results to influence solution design.
Have experience in understanding customer emotions and sentiments which will help you to apply and shape solutions.
Should be hands on with various AI/ML algorithms in categories like classification, correlation, rca,prediction, anomaly deduction, etc., tools for data processing, analysis and visualization,
programming languages and frameworks to derive meaningful insights. (Examples: Python, Spark, R,
Tensor Flow, PyTorch, AWS Kinesis, Redshift,etc).

Roles and Responsibilities:

Develop Code using python for machine learning
Discuss with Engineers, Product Managers to formulate hypotheses, solutions and desired
outcomes.
Act as Subject Matter Expert on ML, Data and AI statistical models and how they apply to
business problems.
You will help to implement models in Machine Learning, Optimization, Neural Networks,
Artificial Intelligence (Natural Language Processing), and other quantitative approaches.
Familiarity with Data Engineering techniques to gather, prepare, cleanse and transform data
for analysis and AI automation, including data pipelines.
Familiarity with getting data from social media - Twitter, Instagram, Reddit, Facebook, etc.
Create prototypes, minimally viable products
Deliver meaningful insights and predictions
Demonstrate business value
Mentor and coach others in the team.

Must Have

Skills:

10+ years of hands-on working experience as Data Scientist with deep understanding of
Machine Learning and AI algorithms
- Linear Regression, Logic Regression, Decision Trees,
K-Nearest Neighbors, Neural Networks, Random Forests, NLP/NLU, etc.
5+ years of experience with different frameworks such as Tensor flow, PyTorch, Keros,
Spark

ML.
4+ years of hands-on coding experience with languages such as Python, R, Scala, Go, etc.
Good experience with source control systems such as git.

Good to Have :
Experience in prompt engineering, RAG system setup, microservices with container
technologies like Docker/Kubernetes

Working experience with using LLM and prompt engineering to solve problem,
Handle on deploying and running services in Kubernetes

Experience with the AWS services (Examples: Sage Maker, Comprehend, Lex, Rekognition,
Transcribe, EKS, Lambda, S3, etc)

Experience with troubleshooting production systems.
Good understanding and use of CICD systems such as Jenkins, Gitlab, etc.

Qualification:

Bachelor's degree in computer science engineering, or a related technical degree.