Machine Learning Engineer

Adobe•San Jose, CA

8d•$125,600 - $234,150

About The Position

Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers. Partnering with the business units, the candidate will be building various products that address challenging business problems through our customers’ full lifecycle, from customer analytics to marketing media optimization. By using statistical and econometric methods, predictive models, experimental design methods, and optimization techniques, the candidate will be working on the research and development of exciting projects like attribution, media mix modeling, budget optimization, personalization, causal analysis, time series analysis. Ideal candidates will have a strong academic background as well as technical skills including applied statistics, machine learning, analyzing data, and software development. Familiarity with working with large-scale datasets and scalable data handling approaches would be a plus.

Requirements

PhD or MS in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, or a related technical field or equivalent industry experience
3+ years of hands-on experience in machine learning engineering or applied data science
Deep understanding of statistical modeling, machine learning, and deep learning with a track record of taking these methods from experimentation to production
Proficiency in Python , experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
Familiarity with statistical modeling and analysis tools (R, MATLAB, or equivalent)
Solid experience with relational databases, SQL, and large-scale data pipelines (Spark, Pandas, or similar)
Experience with the full ML lifecycle: feature engineering, model training, evaluation, deployment, and post-launch monitoring
Strong analytical and quantitative problem-solving ability , comfortable with ambiguity and capable of driving toward a solution independently
Excellent communication skills, able to convey technical findings clearly to both engineering and cross-functional stakeholders, strong collaborator and team player

Nice To Haves

Experience with LLMs, RAG pipelines, or generative AI
Familiarity with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)
Experience with A/B testing and Survival/time-to-event modeling
Knowledge of responsible AI practices (bias detection, model explain-ability)

Responsibilities

Develop predictive models on large-scale datasets to address various business problems with advanced statistical modeling, machine learning, and analytics techniques.
Develop and implement scalable and efficient modeling algorithms that can work with large-scale data in production systems
Collaborate with product management and engineering groups to develop new products and features.