Machine Learning Engineer
Python
Advanced Analytics
Ai Ml
Analytics
Artificial Intelligence
Big Data
Cloud Platform
Cloud Platforms
Data & Ai
Data Analysis
Data Analytics
Data Architecture
Data Integration
Data Mining
Data Pipeline
Data Platform
Data Processing
Data Science
Database
Databases
Databricks
Deep Learning
Detection Engineering
ETL
Feature Engineering
Fraud Analytics
Machine Learning
Machine Learning Engineer
Predictive Analytics
Predictive Modeling
Production Analytics
Statistical Modeling
Job Description
Photon offers an onsite role in New Jersey that emphasizes collaboration, real-world impact, and continuous growth. As a Machine Learning Engineer, you will design and deploy analytics models that address concrete business challenges, partner with product and engineering teams to deliver end-to-end ML solutions, and push models into production. This position centers on practical application of statistics and machine learning using Python, Spark, and Databricks, with the opportunity to influence customer experiences and key business decisions.
Responsibilities
- Analyze business use cases and craft analytics models using appropriate statistical and machine learning techniques tailored to specific needs.
- Develop machine learning algorithms to personalize customer experiences and generate actionable insights.
- Apply data mining and machine learning methods, including forecasting, prediction, segmentation, recommendation, and fraud detection.
- Augment company data by integrating third-party sources to expand analytics capabilities.
- Enhance data collection processes to capture information essential for analytics systems.
- Prepare raw data for analysis by cleaning data, imputing missing values, and standardizing formats using Python data frameworks such as Pandas and NumPy.
- Implement machine learning models with a focus on performance and scalability using PySpark in Databricks.
- Design and build infrastructure to enable large-scale data analytics and experimentation.
- Utilize tools like Jupyter Notebooks for data exploration and model development.
Requirements
- Undergraduate or graduate degree in Computer Science, Mathematics, Physics, or related fields; PhD preferred but not necessary.
- At least five years of experience in data analytics with a solid grounding in core statistical algorithms such as classification and regression.
- Strong experience with Python based machine learning libraries including scikit-learn, TensorFlow, and PyTorch.
- Proficiency with analytics platforms like Databricks for large-scale data processing.
- At least four years of continuous experience with Spark, with emphasis on PySpark.
- Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.
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