Remote Senior Machine Learning Engineer - Enterprise AI

Wwshemi; United States; Remote; USD 173,000 - 183,000; Full time

Benefits offered by this job

Remote work option

Job summary

Instacart’s Enterprise AI organization is hiring a Senior Machine Learning Engineer to design, build, and deploy production ML systems that create measurable business impact. You will own the full ML lifecycle from problem formulation to deployment and monitoring, collaborating with product managers, data scientists, platform engineers, and business partners.

This role rewards strong ML expertise and solid software engineering practices.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 5+ years producing and deploying ML models or systems.
• Proficient in Python and SQL with production-quality code.
• Experience with cloud platforms (GCP or AWS).
• Experience with Docker, CI, monitoring and incident response.
• Ability to collaborate with product, engineering, data science and business stakeholders.

Responsibilities

• Design, implement, and deploy ML models and services for Enterprise AI.
• Own the full ML lifecycle from problem formulation to production monitoring.
• Build scalable Python software with tests, profiling and documentation.
• Partner with cross-functional teams to define success metrics and outcomes.
• Develop ML services on cloud infrastructure with observability and safeguards.
• Use experiments and evaluation methods to guide decisions.
• Contribute to engineering direction through design reviews and tradeoffs.
• Mentor colleagues and support operational reliability of services.

Skills

Python

SQL

Automated testing

Cloud platforms

Docker

CI/CD

Monitoring

Incident response

Stakeholder management

Education

Bachelor's in CS or related

Master's or PhD in CS

Tools

Kubernetes

Airflow

Spark

Go

Job description

Instacart’s Enterprise AI organization is hiring a Senior Machine Learning Engineer to design, build, and deploy production ML systems that create measurable business impact. You will own the full ML lifecycle from problem formulation to deployment and monitoring, collaborating with product managers, data scientists, platform engineers, and business partners.

This role rewards strong ML expertise and solid software engineering practices.