Senior Machine Learning Engineer

Vor 3 Tagen

Sydney, Österreich FIS Global Vollzeit

Position Type :

Full time

Type Of Hire :

Experienced (relevant combo of work and education)

Travel Percentage :

0%

Are you curious, motivated, and forward-thinking? At FIS youâll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. FIS is a leading Fintech provider with wide range of Products and Services. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role

 

FIS is seeking an experienced and dynamic MLOps engineer, who will be a subject matter expert in the development of a Cloud Based solution/product. You will have at least 5 years of experience in Machine Learning & ML OPS and proven experience in deploying model on Azure Cloud. Masters is Data Science or Machine learning & experience in Fintech Capital market space is an added advantage.

 

What you will be doing:

  • Participating in Daily Scrum for developing Machine learning solution. Working in Agile development framework

  • Understanding the business problems and working with various business & Technical stakeholders.

  • Doing exploratory Data analysis and understanding meta data.

  • Creating and reviewing ML Models.

  • Understanding on Supervised Learning, Unsupervised Learning and Reinforcement learning

  • Understanding on Generative AI and prompt engineering

  • Model fine tuning.

  • Partnering with Data Engineers, ML engineers, developers, and business teams to test your models in production.

  • Building and maintaining operational tools for deployment, monitoring, and analysis of Azure infrastructure and systems.

  • Administering and troubleshooting Linux based, Dockerized, Kubernetes-orchestrated systems.

  • Maintaining/Supporting the solution post development.

 

What You Will Need:

  • Experience with Time Series forecasting Models: ARMA, ARIMA, SARIMA, Vector Auto regression, Smoothing, Kalman Filtering,

  • Anomaly Detection: Isolation forests, SVM, Decision Trees and Ensemble Learning

  • Deep Learning Basics: RNN, LSTMs, Transformer Architecture, BERT, GPT, Roberta

  • Generative AI Prompt engineering: Defining & working on prompts, Fine Tuning LLMs, RAG

  • Lang Chain: Chain, Prompts, Agents, Vector stores, Document loaders

  • Deploying ML Model on Cloud: Model end point deployment, Docker, Understanding REST APIs, Bit bucket

  • Cloud Azure Services: Chat GPT 3.5 Turbo, Azure AI Search, Azure Content Safety, Cosmos DB, Blob storage, Data Bricks, Azure Kubernetes services, Experience in creating ML pipelines on Azure.

  • Good Communication Skills: Listening, Comprehending, Speaking.

  • Understanding of Application Architecture/Microservices: Application Architecture, Microservice based Architecture.

  • Programming: Python, SQL; familiar with Python Libraries like SCIKIT Learn, Tensorflow, Keras, pytorch, scikit-learn, seaborn , matplotlib

 

Added bonus if you have:

  • Experience Working in the financial industry.

 

What we offer you

  • An opportunity to make your mark in a world leading global Fintech

  • A flexible hybrid environment with a broad spectrum of opportunities

  • A competitive salary package with medical and personal insurances and employee shareholding

#LI-TC2

 

Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

#pridepass

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