Machine Learning Engineer

Adobe

Quick summary

Work type: On-site
Location: San Jose
Salary: $161,700–$234,150 / yr
Posted: 10 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $217k

This role $198k

$150k most similar roles pay here $274k

This role pays less than 68% of similar roles. Most pay $184,150–$249,750 — the shaded band above. At the midpoint, this role pays about $198k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 344 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 344 roles with salary data.

Most-posted roles

View all roles at Adobe

At a glance

TL;DR · Machine Learning Engineer

Apply Now Log in to save

Adobe seeks a Machine Learning Engineer to join its dynamic team, focusing on applying AI and machine learning techniques to large datasets to enhance customer experiences across the full lifecycle. This role involves developing predictive models and scalable algorithms for production systems, collaborating closely with product management and engineering teams to innovate new products and features such as attribution, media mix modeling, budget optimization, personalization, and causal analysis. Ideal candidates should possess a PhD or MS in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, or Econometrics, along with 0-2+ years of experience in relevant fields. Strong skills in statistical modeling, machine learning, deep learning, Python, Scala, Java, C, R, Matlab, and SQL are essential, as is the ability to work effectively within a team environment.

Skills

Python Scala Java C R Matlab scikit-learn SQL AWS Kubernetes Docker CI/CD Git Jupyter Notebook TensorFlow PyTorch PostgreSQL MongoDB Hadoop Spark BigQuery Snowflake

What you'll do

Develop predictive models on large-scale datasets using advanced statistical and machine learning techniques.
Implement scalable modeling algorithms for production systems to address business challenges.
Apply econometric methods, experimental design, and optimization techniques in research projects.
Work on attribution, media mix modeling, budget optimization, personalization, and causal analysis initiatives.
Collaborate with product management and engineering teams to create new products and features.

What we're looking for

PhD or MS in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, Econometrics required.
0-2+ years of experience in statistical modeling, machine learning, deep learning, and analytics.
Proficient in Python, Scala, Java, C, R, Matlab, scikit-learn, and SQL.
Strong analytical skills with a track record of solving complex business problems using advanced techniques.
Experience developing scalable and efficient algorithms for large-scale data production systems.
Excellent communication and teamwork skills to collaborate across product management and engineering groups.

Hybrid

Save