Machine Learning Engineer

4 weeks ago

Chicago, United States Compunnel Inc. Full time

Role: Machine Learning Engineer

Location: Chicago, IL- 3 days Hybrid onsite in a week

Interview: 2 steps, would like candidates to highlight contributions they've made to teams and projects they've worked on as it relates to solving ML challenges

Hybrid onsite, in Chicago 2-3x a week


Notes:

  • They are maturing ML Operations
  • Framework is built on top of SageMaker for model building and deployment
  • They want to enhance this framework and implement new tools into their pipeline
  • Focused mainly on ML Operations for this candidate
  • AWS Cloud experience required
  • Thinking about automating processes
  • Experience fine-tuning LLMs


PURPOSE:

  • 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 client 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 isn’t just a nice to have, it’s 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 client 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.


EDUCATION:

Master’s degree in computer science, software engineering, or related fields required

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