Senior Machine Learning Engineer

Summary

Join Instacart as a Senior Machine Learning Engineer and design, develop, test, and deploy machine learning models focused on recommendations and ranking. Build scalable ML services, take ownership of the entire development lifecycle of machine learning solutions, and stay at the forefront of machine learning advances. Collaborate with software engineers and product managers to define and influence features. This role is remote, offering flexibility and competitive compensation and benefits, including equity grants and annual refresh grants. Base pay varies by location. Instacart prioritizes ownership, customer focus, and fast-paced innovation.

Requirements

• Advanced degree (Master’s or PhD) in AI / Machine Learning, or 3+ years of industry experience in machine learning
• Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
• Strong analytical skills and a proven ability to deploy ML models in production environments with tangible business impact
• Self-motivation and a strong sense of ownership

Responsibilities

• Design, develop, test, and deploy machine learning models focused on recommendations and ranking
• Build scalable ML services to facilitate the deployment of models at a large scale
• Take ownership of the entire development lifecycle of machine learning solutions, from ideation and design to deployment and maintenance, ensuring delivery with speed and efficiency
• Stay at the forefront of machine learning advances, including generative AI, LLMs, and innovative recommendation technologies
• Collaborate with software engineers and product managers to define and influence features that address customer challenges

Preferred Qualifications

• Advanced degree (Master’s or PhD) in AI / Machine Learning with 5+ years of industry experience applying machine learning to real-world, large-scale datasets
• Expertise in deep learning frameworks, generative AI, or LLMs
• Specialized knowledge in personalization, recommendation systems, learning-to-rank or NLP technologies
• Experience with training large-scale models and model deployment on cloud services (Docker, AWS/GCP/Azure)
• Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
• Strong analytical skills and a proven ability to deploy ML models in production environments with tangible business impact
• Self-motivation and a strong sense of ownership

Benefits

• Highly market-competitive compensation and benefits
• Remote work
• Equity grant
• Annual refresh grants