Photon is seeking a seasoned Machine Learning Engineer to design and deploy analytics-driven models that solve real business problems. The role is based in New Jersey with onsite collaboration, and you will partner with product and engineering teams to deliver end-to-end ML solutions, deploy models into production, and leverage Python, Spark, and Databricks to generate actionable insights.
Responsibilities
- Analyze use cases and design analytics models using statistical and machine learning methods tailored to specific business needs.
- Develop machine learning algorithms aimed at personalizing customer experiences and extracting actionable business insights.
- Apply data mining and machine learning techniques across forecasting, prediction, segmentation, recommendation, and fraud detection.
- Augment company data by integrating third‑party data sources to enhance analytics capabilities.
- Improve data collection processes to capture information essential for analytics systems.
- Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing formats using Python libraries such as Pandas and NumPy.
- Implement scalable machine learning models with attention to performance, using tools like PySpark in Databricks.
- Design and build infrastructure that supports large-scale data analytics and experimentation.
- Utilize Jupyter Notebooks for data exploration and model development.
Requirements
- A bachelor's or master's degree in Computer Science, Mathematics, Physics, or related fields; a PhD is preferred but not required.
- Minimum of 5 years of experience in data analytics, with a solid grasp of core statistical algorithms including classification and regression.
- Strong experience with Python-based machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
- Proficiency with analytics platforms like Databricks for large-scale data processing.
- At least 4 continuous years of experience with Spark, particularly using PySpark.
- Hands-on experience with data processing and analysis tools such as Pandas, NumNum?
Technologies
- Python
- Spark
- Databricks
- Pandas
- NumPy
- Jupyter Notebooks
- PySpark
- scikit-learn
- TensorFlow
- PyTorch