Summary
Join Instacart's team of Senior Machine Learning Engineers and contribute to enhancing real-time recommendation algorithms, designing feed ranking systems, and improving personalized discovery. You will design, develop, test, and deploy machine learning models focused on recommendations and ranking, building scalable ML services for large-scale deployment. This role requires ownership of the entire development lifecycle, from ideation to maintenance, and staying current with machine learning advancements. Collaboration with software engineers and product managers is key to defining features addressing customer challenges. Instacart offers a flexible work environment and competitive compensation and benefits, including equity grants.
Requirements
- Advanced degree (Masterβs 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 (Masterβs 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)
Benefits
- Highly market-competitive compensation and benefits
- Remote work
- New hire equity grant
- Annual refresh grants
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