Senior Machine Learning Engineer (AdTech)

PulsePoint; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

401(k) match

Medical, dental, vision insurance

Life & disability insurance

Tuition reimbursement

Paid vacation & holidays

Team-building events

Job summary

PulsePoint is seeking a Senior Machine Learning Engineer, AdTech, to optimize real-time bidding strategies and auction mechanics, ensuring efficient spend and campaign targets. You will build and refine event-prediction models, engineer features such as user embeddings and cross-device signals, and contribute to production data pipelines.

Join a team that values advanced ML methods, rigorous analysis, and collaboration across teams to drive measurable advertising results.

Qualifications

• Minimum 5 years of experience in machine learning and data science.
• Strong knowledge of Python and DS packages (NumPy, Pandas, Scikit-Learn).
• Experience with algorithms and data structures; time and space complexities.
• Experience with real-time bidding or online advertising tech is a plus.
• Solid understanding of statistical methods and ML techniques.

Responsibilities

• Analyze and optimize real-time bidding strategies and auction mechanics.
• Develop and improve models for event prediction and feature engineering.
• Explore user embeddings, cross-device signals, and cookieless identification.
• Maintain and extend production ML code for data integration and model support.
• Mine diverse data sources to improve campaign targets.

Skills

Python

Algorithms

Optimization

NLP

Data Mining

Statistical Analysis

Neural Networks

Generalised Linear Regression

Multiclass Classification

Java

RTB/Online tech

Probability & Statistics

Dimensionality Reduction

Tools

NumPy

Pandas

Scikit-Learn

TensorFlow

Job description

• As a member of our Data Science Engineering team, the Sr. Machine Learning Engineer, AdTech will focus on optimizing real-time bidding strategies and auction mechanics to efficiently spend ad budgets and deliver against campaign targets
• Analyzing and optimizing real-time bidding strategies and online auction mechanics
• Developing new or improving existing models of event predictions
• New feature engineering for multiple machine learning models:
• User embeddings and clustering; fraud detection, etc
• Cross-device user identification, cookieless mechanisms development
• Mining different data sources
• Supporting existing codebase for data integration and production support for our core models

Benefits

• Dollars and Sense: 401(k) match
• Happy + Healthy: Comprehensive medical plans, affordable medical, dental and vision options, 100%-paid life & disability insurance
• Break a Sweat: Free virtual fitness classes, Better Yourself Wellness program
• Always Learning: Generous annual tuition reimbursement, ongoing team trainings
• Take a Load Off: Paid vacation, sick time, and company holidays (including a floating holiday)
• Good Ol' Fun: Team-building events, happy hours, holiday celebrations, and more!

5 years minimum of experience in machine learning/data scienceAlgorithms and Data Structures (e.g., sorting, search tree, binary heap, trie; time & mem complexities of algorithms)Advanced knowledge of Python using standard DS packages (numpy/pandas/scikit, etc.); Being able to optimize and speed-up codeKey Skills: Python, Algorithms, Optimisation, NLP, Data Mining, Statistical Analysis, Neural Networks, Generalised Linear Regression, Multiclass Classification, Java, R3+ years of RTB Auction or similar online technologiesProbability and Statistics (e.g., hypothesis testing; Markov process and its stationary distributions, stochastic matrix and its properties; Bayesian inference)ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 regularisation, Decision trees and their ensembles, collaborative filtering, Thompson sampling / MCMC, Neural Networks, etc.)