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Senior Machine Learning Engineer in Chicago , IL (EAD or GC or Citizen) at Chicago, Illinois, USA
Email: [email protected]
From:

Bhuwan Tiwari,

Sonitalent Corporation

[email protected]

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Job title: Senior Machine Learning Engineer

Location: Chicago , IL ( Chicago  local preferred )

Interview: Phone/ Skype

Visa: No H1B, CPT&OPT

Must have 12+Years experience 

Job Descxription:

At Client, were working to Advance Care through data-driven decisions and automation.  This mission serves as the foundation for every decision as we create the future of travel. We cant do that without the best talent talent that is innovative, curious, and driven to create exceptional experiences for our guests, customers, owners and colleagues.

Client seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest experience and drive efficiencies across the operations of our business.

In this role you will design and implement algorithmic product architectures to bring our machine learning models to life across the full lifecycle of the product including data ingestion, ML processing, and results delivery/activation. This role will work cross-functionally with various data science teams, data engineering teams, and data architecture teams. The ideal candidate can serve as both solutions architect as well as hands-on implementation engineer and guide the team towards best-in-class algorithmic product implementations.

You will be a part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about data science.

Applying the latest techniques and approaches across the domains of data science, machine learning, and AI isnt just a nice to have, its a must.

POSITION RESPONSIBILITIES:

       Partner with data scientists to design workflows/architectures that activate ML models and maximize their impact, such as real-time streaming use-cases and offline batch optimizations.

       Partner with data scientists to develop prototype solutions of algorithmic products leveraging appropriate AWS services with appropriate consideration for scale and latency where applicable.

       Implement and productionize final solutions via infrastructure-as-code pattern.

       Implement data processing workflows to enhance our Feature Store with impactful data including appropriate data cleansing/imputation logic.

       Enhance existing algorithmic products architecture/workflow as needed to maximize impact of the algorithmic product.

       Partner with data engineering team to ensure data science data needs are being delivered in the appropriate format/cadence required for maximum impact.

       Stay up to date with latest design patterns and AWS services with respect to Machine Learning Engineering.

       Partner with data architecture, data governance, and security team to ensure solutions meet required standards.

The ideal candidate demonstrates a commitment to Hyatt core values: respect, integrity, humility, empathy, creativity, and fun.

EXPERIENCE AND QUALIFICATIONS:

       5+ years of implementing software product solutions in a cloud environment with a focus on algorithmic/machine learning products, hospitality experience not required

       Expertise in AWS cloud services

       Expertise in Python, SQL, PySpark, Docker

       Experience with streaming and batch data architectures at scale

       Experience operating in an Agile Methodology environment.

       Experience with DevOps and CI/CD concepts

       Excellent communication and teamwork skills

       Position will not require customer-facing interactions.

                         Thanks, 

Bhuwan Tiwari

Sr.Technical Recruiter 

SoniTalent Corporation I

5404 Merribrook Lan--e, Prospect, KY, USA

Cell - 859-946-4266 | [email protected]

Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology Illinois Kentucky
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Thu Dec 14 02:11:00 UTC 2023

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