ML Engineer

 
Must have - Proficiency Python Programming, Strong knowledge of Linux operating systems
Extensive knowledge of AI supervised, unsupervised, GenAI LLM and Python libraries to perform data analysis, building advanced machine learning models and data integrations with source systems
Implement AI-based clustering models using DBSCAN to group events by spatial and temporal dimensions in real time.
Design APIs for performance, real-time applications, scale, ease of use and governance automation.
Training ML models to effectively communicate complex data insights through clear and informative visualizations
Knowledge and experience in Cloud Environments (AWS, Azure, GCP), specifically to AWS EC2, Kinesis, S3, and Lambda.
Experience in building and deploying end to end real time streaming data pipelines using cloud and docker services, experience with Kubernetes
Strong knowledge of CI/CD, test automation and DevOps
Ability to integrate data, sourcing data from several Sources including databases, files, API and Server logs.
Drive requirements for AI related projects, work with internal customers and with ServiceNow and Salesforce Product Managers for features planning, prioritization and implementation
Strong quantitative and statistical skills
Apply GenAI, ML and DL concepts, NLP in real world applications to solve business problems
Develop application-specific interfaces that leverage GenAI capabilities and LLMs
Familiarity with common frameworks such as PyTorch, TensorFlow, Keras, NLTK, or spaCy
Familiarity and experience with Databases like Postgres, Redshift, MySQL