to join our team and drive data-driven decision-making across our digital platform. Apply now to be part of the team.
Responsibilities:
ML Model Development:
Apply advanced machine learning techniques to understand customer behavior, drive product adoption, and improve user engagement.
Pipeline Design & Implementation:
Design, build, and maintain scalable machine learning pipelines to support product development and evidence-based decision-making.
Cross-functional Collaboration:
Partner with senior leaders across Product, Engineering, Product Marketing, and Design to ensure effective use of ML models for business impact.
Data Analysis & Insights:
Use data science and quantitative analysis techniques to influence product strategy, roadmap prioritization, and user experience improvements.
Technical Leadership:
Mentor and guide junior team members, ensuring best practices in model development, coding, and production deployment.
ML-Driven Features:
Deliver key ML-powered features for our Digital Customer Platform, ensuring high scalability, performance, and reliability.
Minimum Qualifications:
Educational Background:
MS/PhD in Mathematics, Statistics, Computer Science, Physical Sciences, or a related quantitative field.
Experience:
5+ years of industry experience working on ML-based solutions, from concept to production.
Technical Skills:
+ Proficiency with machine learning libraries and frameworks (
TensorFlow, PyTorch, Scikit-learn, etc.)
.
+ Hands-on experience with Large Language Models (
LLMs
),
RAG
(Retrieval-Augmented Generation), and
Generative AI
.
+ Expertise in Natural Language Processing (
NLP
) for text analysis and understanding.
+ Experience with big data platforms (
Hadoop, Spark, Hive
) and cloud environments (
AWS
preferred).
+ Strong
SQL
and
NoSQL
database skills.
+ Proficiency in at least one programming language (
Python
or
Java
).
+ Experience with MLOps tools and techniques to streamline ML workflows and production deployment.
APPLY NOW
!
NearSource Technologies
values diversity and is committed to equal opportunity. All qualified applicants will be considered regardless of their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as protected veterans.
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