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Lead Machine Learning Engineer (Recommendation Systems)

Conch Technologies
New York, NY, United States
16 days ago
Apply on www.careerjet.com
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
www.careerjet.com

Tech stack

Amazon Web Services Python (Programming Language) Machine Learning Recommender Systems Tensorflow Pytorch Scikit Learn Kubernetes Machine Learning Operations Databricks

Job description

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agi…

  • 2 days ago

Requirements

  • Must have experience building and deploying production-grade ML systems.
  • Strong hands-on experience with Databricks, MLflow, Python,TensorFlow/PyTorch/Scikit-learn.
  • Experience supporting real-time inference and model serving.
  • Built recommendation systems in hospitality, gaming, loyalty, retail, eCommerce, travel, entertainment, streaming, or consumer-facing organizations.
  • Experience with Customer 360, customer segmentation, loyalty programs, propensity models, customer lifetime value

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

1:39 min

Fundamentals of tensors and the TensorFlow library

Håkan Silfvernagel · LIVE

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · World Congress 2022

2:40 min

Understanding real-world recommendation systems in common platforms

Julian Joseph · LIVE

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · World Congress 2026 Europe

1:50 min

Real life recommendation systems and final project conclusions

Lutske van der Meer Lutske van der Meer · World Congress 2024

Videos

See all
How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale) thumbnail
27:23
World Congress 2023 • almost 3 years ago

How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)

Dora Petrella

Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding) thumbnail
29:32
World Congress 2026 Europe • about 2 months ago

Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)

Christoph Lohrmann, Utz Bacher

Machine learning in the browser with TensorFlowjs thumbnail
38:24
LIVE • over 5 years ago

Machine learning in the browser with TensorFlowjs

HÃ¥kan Silfvernagel

Understanding Kubernetes in a visual way thumbnail
29:05
World Congress 2026 Europe • about 2 months ago

Understanding Kubernetes in a visual way

Aurélie Vache

Serverless deployment of (large) NLP models thumbnail
39:02
LIVE • over 5 years ago

Serverless deployment of (large) NLP models

Marek Suppa

Data Science in Retail thumbnail
58:21
LIVE • over 3 years ago

Data Science in Retail

Julian Joseph

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