Senior Machine Learning Engineer II, Ads Response Prediction

SpaceX

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$240,000–$253,500 / yr
Posted
7 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $219k
This role $247k
$168k most similar roles pay here $273k

This role pays more than 66% of similar roles. Most pay $177,875–$260,150 — the shaded band above. At the midpoint, this role pays about $247k versus about $219k for comparable roles.

Based on 240 similar postings.

Employer

About SpaceX

SpaceX designs, manufactures, and launches advanced rockets and spacecraft with the mission of enabling humans to become a multi-planetary species. It operates the Falcon 9, Falcon Heavy, and Starship launch vehicles, as well as the Starlink satellite internet constellation.

SpaceX currently has 604 open roles on FindRole.

Listed pay typically runs $130,000–$155,000 across 440 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Engineer II, Ads Response Prediction

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As a Senior Machine Learning Engineer II on Instacart’s Ads Response Prediction team, you will lead the development of core ML models that enhance ad relevance and customer engagement. Your daily tasks include formulating theoretical problems, mitigating biases in training data, and advancing model accuracy across various platforms. You’ll work with cutting-edge technologies like TIGER for generative retrieval systems and Semantic ID representation learning to improve ads ranking and incrementality. The team leverages robust ML infrastructure including Delta/DBT-Spark pipelines and Ray-based distributed training, allowing you to focus on modeling science. Ideal candidates have a PhD or Master’s in machine learning or related fields, with extensive experience in large-scale prediction problems. Proficiency in Python, deep learning frameworks like PyTorch and TensorFlow, and data manipulation tools such as SQL and Pandas is essential.

Skills

Python PyTorch TensorFlow JAX DeepFM DCN Multi-task_learning Causal_inference Counterfactual_reasoning SQL Spark Pandas CI/CD Mixture_of_Experts Transformer_layers LoRA_adapters Semantic_IDs Autoregressive_sequence_models LLM-driven_approaches AutoML

What you'll do

  • Lead the design and development of pCTR and conversion prediction models to improve calibration.
  • Implement debiasing techniques like Mixed Negative Sampling (MNS) and Inverse Propensity Weighting (IPW).
  • Contribute to next-generation Multi-Domain Multi-Task (MDMT) model architecture innovations.
  • Drive sequence modeling initiatives, expanding TIGER generative retrieval system applications.
  • Formulate ambiguous modeling problems into well-defined ML research directions with clear criteria.

What we're looking for

  • PhD or Master's in machine learning, statistics, computer science, or related field.
  • 6+ years of experience applying ML to ranking, recommendation, or prediction problems.
  • Deep understanding of CTR/conversion prediction modeling and multi-task learning formulations.
  • Strong foundation in causal inference, counterfactual reasoning, and bias mitigation techniques.
  • Proficiency in Python, deep learning frameworks (PyTorch, TensorFlow, JAX), and data manipulation tools.

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