In this role you will get to:

• Partner with product management to identify challenges, scope ML opportunities, and design solutions

• Understand business requirements and present technical solutions to non-technical team members

• Collaborate with engineering, data science, and product teams to implement ML and GenAI solutions in production environments

• Evaluate and improve existing machine learning models

• Leverage Google Cloud Platform and VertexAI for model training and deployment

• Enhance ML infrastructure and tools to align with industry best practices.

• Manage the end-to-end lifecycle of ML models, including serving, monitoring, and updating models in production.

• Design and implement scalable, low-latency ML model deployment pipelines. 

• Design self-service CI/CD pipelines to democratize ML deployment, enabling teams at organizational level.

• Work with big and novel data by data wrangling, feature engineering, model building, and visualization

• Design frameworks to efficiently process large-scale streamed data from upstream and downstream applications for testing and building ML models.

• Build DAGs, ETL pipelines, perform exploratory data analysis, and develop scalable solutions

• Technologies used: Python, Tensorflow, Pytorch, Spark, Langchain, Pandas, Spacy and many other tools and libraries need for CI/CD like githubActions, terraform, composer, dataproc 

Who you are:

• Masters or PhD qualification in a quantitative field such as Computer Science, Machine Learning/ AI, Mathematics, Physics, Statistics, etc.

• 3+ years of commercial/academic experience with demonstrated technical skills in one or more of the following areas: NLP, Classification, Statistical Modelling, Deep Learning, GenAI, and Forecasting

• Professional experience developing, deploying, and evaluating machine learning in an industrial setting, with a track record of delivering impactful results

• Proficient developing in Python, SQL

• Experience with ML/AI Frameworks and tools: PyTorch, Tensorflow, Sci-kit Learn, XGBoost, Pandas, Numpy and Flask, Langchain, Spark/Pyspark, Langchain

• Experience with Google Cloud Platform - Vertex AI or other cloud platforms for ML implementation

• Experience working with BigQuery, Composer, DAGs, Spark/Pyspark and other data tools

• Experience working with terraform, composer, dataproc and github workflows.

• Eagerness to learn new techniques, technologies, solve problems and contribute in a team environment

• Great interpersonal skills and experience working with cross functional teams

• Illustrated history of living the values necessary to Priceline:  Customer, Innovation, Team, Accountability and Trust. 

• The Right Results, the Right Way is not just a motto at Priceline; it’s a way of life. Unquestionable integrity and ethics is essential.