Senior ML Engineer – Build GenAI-Driven Personalization

Bloomreach; United States; Remote; USD 57,000 - 72,000; Full time

Benefits offered by this job

Stock options

Performance bonus

Education budget

Volunteer days

Flexible remote work

Job summary

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to design and implement cutting-edge AI and GenAI driven algorithmic components for contextual personalization, predictions and behavioral insights that personalize digital experiences.

We enable flexible work arrangements across regions, with offices in Europe, and opportunities to work from anywhere for the specified region, plus collaboration with a strong engineering team on large-scale data.

Qualifications

• BS/MS in Computer Science or related field with strong math foundation.
• 3+ years building ML-driven, scalable algorithms in corporate or startup settings.
• Experience with Generative AI and GenAI stack is a strong plus.
• Proficient in Python, SQL, and cloud-based data processing (BigQuery).

Responsibilities

• Design, develop, and enhance ML/AI models for contextual personalization.
• Process historical data, catalogs, and user behavior to extract features.
• Research cutting-edge ML techniques and run quick proofs of concept.
• Collaborate with ML Engineers to deploy scalable production ML components.
• Stay current with state-of-the-art AI/ML research and conferences.

Skills

Python

ML

GenAI

NLP

SQL (BigQuery)

PyTorch/Keras

Cloud (AWS/GCP/Azure)

Data Modeling

Education

BS/MS in Computer Science or related

Tools

BigQuery

PyTorch

TensorFlow

Job description

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to design and implement cutting-edge AI and GenAI driven algorithmic components for contextual personalization, predictions and behavioral insights that personalize digital experiences.

We enable flexible work arrangements across regions, with offices in Europe, and opportunities to work from anywhere for the specified region, plus collaboration with a strong engineering team on large-scale data.