Machine Learning Engineer

Peterson Technology Partners Ptp
United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$176,800.0 - $228,800.0
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence Amazon Web Services Cloud Computing Data Architecture Data Cleansing Information Engineering Data Governance Software Design Patterns DevOps Python (Programming Language) Machine Learning
+10 more
Software Engineering SQL Databases Data Streaming GaBi Software Data Ingestion AI Platforms Pyspark Information Technology Data Pipelines Docker

Job description

Our client seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that 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 core values: respect, integrity, humility, empathy, creativity, and fun., To provide a consistent, fair, and flexible experience for all candidates, we use AI-assisted tools to support parts of the interview process. This includes our proprietary AI platform Pete & Gabi, which includes AI recruiter Rebecca.

These AI hiring tools help us:

  • Conduct recorded video interviews
  • Transcribe interviews
  • Summarize candidate responses
  • Generate job-related insights
  • Streamline communication and scheduling

Please note that:

The AI does NOT make hiring decisions; all decisions are made by our human recruiters, hiring managers, or client partners.

The AI does not evaluate facial expressions, emotions, or physical traits; it is used only to support fairness, consistency, and efficiency.

If you prefer a non-AI interview format, we will gladly provide an alternative.

Technical or Case Interviews (Role-Dependent):

When applying for certain tech jobs, you may participate in:

  • A technical interview
  • A coding challenge
  • A case study
  • A client-specific assessment

We will always explain what to expect in advance so you can prepare with confidence.

Human Review & Selection:

Every candidate’s profile including interviews, conversations, and assessments is reviewed by experienced recruiters and hiring leaders.

AI insights may assist with organization and evaluation, but final decisions are always human-driven.

Requirements

  • 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

Benefits & conditions

Salary/Rate: $85-$110/HR (depends on experience level). This is a contract position with candidates expected to work 40 hours/ week.

About the company

Peterson Technology Partners (PTP) is an Equal Opportunity Employer committed to creating a transparent, inclusive, and human-centered hiring experience.

For more than 28 years, PTP has operated as one of the top IT staffing and recruiting firms in the USA built on trust, long-term partnerships, and technical excellence.

Based in the Chicago suburb of Park Ridge, IL, our team of more than 500 employees and consultants is dedicated to, For more than 28 years, PTP has focused on putting people first candidates, consultants, employees, and clients.

We’re committed to a hiring process that is:

  • Transparent
  • Compliant
  • Equitable
  • Powered by innovative technology that enhances not replaces human judgment

Welcome to the future of hiring at Peterson Technology Partners.

Apply for this position

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