Role overview
* 10+ yrs experience minimum
* Collaborate and manage with
**data science**
,
**engineering**
, and
**GenAI teams**
to deploy and scale machine learning and generative AI models.
* **Operationalize complex ML and GenAI models**
into production environments, ensuring end-to-end deployment and monitoring.
* Apply knowledge of
**standard ML algorithms**
(Regression, Classification),
**NLP concepts**
(sentiment analysis, topic modeling, TF-IDF), and
**Generative AI techniques**
(LLMs, prompt engineering, embeddings).
* Apply knowledge of
**Retrieval Augmented Generation**
using embedding models and Vector databases.
* Manage delivery of
**GenAI/LLM features**
(prompt engineering, evaluation metrics, retrieval patterns, guardrails) and productionizing Q&A/assistant workflows.
* Lead Platform and DevOps: CI/CD, containerization, observability, and environment automation in a major cloud - ideally working experience on
**Google**
.
* Utilize
**Python**
and ML/GenAI libraries such as
**scikit-learn**
,
**PySpark**
,
**pandas**
and
**Hugging Face Transformers**
for model development and optimization.
* Design, develop, and maintain
**adaptable data pipelines**
tailored to use-case-specific requirements.
* Integrate ML and GenAI use cases into
**business workflows**
, ensuring seamless data exchange with upstream and downstream systems.
* Build and maintain pipelines for
**model performance metrics**
, supporting Model Risk Oversight and compliance review cadences.
* Develop
**runbooks**
and provide ongoing support for operationalized models to ensure reliability and scalability.