Machine Learning Engineer[C2C/W2 ROLE]

Save Mart Supermarkets LLC
Philadelphia, United States of America
23 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 333K

Job location

Philadelphia, United States of America

Tech stack

Big Data
Distributed Systems
Python
Machine Learning
Performance Tuning
TensorFlow
Standard Sql
Software Deployment
Large Language Models
PySpark
Scikit Learn
Machine Learning Operations
Data Pipelines
Docker

Job description

  • Model Development: Design, build, train, and fine-tune machine learning and deep learning models for real-world use cases
  • Production Deployment: Deploy, monitor, and maintain ML models in production environments
  • Data Pipeline Development: Build and optimize scalable data pipelines for ingestion, transformation, and processing
  • Performance Optimization: Evaluate models using metrics like accuracy, recall, and AUC; optimize for performance and scalability
  • Collaboration: Work closely with cross-functional teams including data engineers, software engineers, and business stakeholders

Requirements

We are seeking a hands-on Machine Learning Engineer with 5+ years of experience who can design, build, and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced, engineering-focused environment., * 5+ years of experience as a Machine Learning Engineer or similar role

  • Strong Python programming skills with solid software engineering fundamentals
  • Recent and hands-on experience with PySpark (mandatory)
  • Experience with machine learning frameworks such as Scikit-learn
  • Strong understanding of statistics, probability, and algorithms
  • Experience working with SQL, data modeling, and large datasets
  • Proven track record of deploying ML models into production environments
  • Experience with AWS services

Preferred Qualifications

  • Experience with MLOps tools such as Docker for model deployment
  • Hands-on experience with local Large Language Models (LLMs)
  • Familiarity with distributed computing and big data technologies, * Technical discussion
  • Live coding exercise (Video ON + full desktop screen sharing required)

Round 2 (60 mins In-Person Preferred)

  • Technical deep dive
  • Advanced live coding exercise

Benefits & conditions

  • $160.00 per hour Join a dynamic network of Machine Learning Engineers and connect with top AI labs and companies seeking your expertise. This opportunity allows you to apply once and be considered …

  • Just now

About the company

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