Machine Learning Engineer II, Content AI

Key Skills

Aartificial intelligence, Analytical and Problem solving, ArcCatalog, Computer Vision (CV), Effective communication skills, Forecasting, Machine learning techniques, Natural Language Processing (NLP), Pandas, Scikit-learn, SPARK Programming, SQL, TensorFlow, XGBoost

Job Description

We're looking for mid level machine learning engineers who have a strong foundational understanding of ML concepts to join our team. We work on a range of interesting and challenging problems, from ensuring deliveries are efficient and on-time to helping customers decide what to buy. Machine learning is at the heart of this effort and an essential ingredient in Instacart's aggressive growth plan and vision for the future.

As Instacart grows and takes on more challenging ambitions, we look to engineers to raise the level of execution overall with both depth of knowledge and broad influence. In addition, they are strong communicators, and effective cross-functional operators.

ABOUT THE ROLE

• This is an individual contributor role with significant impact within the machine learning and product teams
• You will collaborate with Staff Machine Learning Engineers and Product Managers to influence features and projects
• Design, develop, test, and deploy machine learning models to solve customer problems and drive business forward
• Stay up-to-date with the latest technologies and advancements in ML
• Assist in designing ML services capable of large-scale model development

ABOUT YOU

MINIMUM QUALIFICATIONS

• Have a graduate degree (masters or PhD) in artificial intelligence, machine learning or equivalent self study and experience
• Have strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
• Have strong analytical skills and problem-solving ability
• Are a strong communicator who can collaborate with diverse stakeholders across all levels

Preferred Qualifications

• 1-2 years of industry experience developing machine learning models with business impact, and shipping ML/AI solutions to production.

Strong expertise in one or more of the areas:

• Personalization, recommendation systems, knowledge graphs, and catalog management.
• Natural Language Processing (NLP), large language models, generative AI, conversational AI, and computer vision.