MLOps Engineer: Scale AI Pipelines & Platforms

Kensho Technologies; New York (NY); Vor Ort; USD 120.000 - 150.000; Vollzeit

Benefits dieser Stelle

Medical, Dental, and Vision insurance

Unlimited Paid Time Off

26 weeks paid Parental Leave

401(k) plan with employer matching

Tuition assistance for degree programs

Snacks and drinks provided

Dog-friendly office

Bike sharing program memberships

Mentoring and learning opportunities

Networking opportunities at conferences

Zusammenfassung

An innovative tech company in New York is seeking a member for their MLOps team. This role involves developing tools and services to enhance the ML workflow, while closely collaborating with ML engineers to identify challenges and provide effective solutions. The ideal candidate will have over 2 years of experience in ML infrastructure, strong Kubernetes and Python skills, as well as a good understanding of cloud platforms like AWS. They will also help train teams on best practices and promote efficient processes in ML product development.

Qualifikationen

• 2+ years of experience in ML infra, ML Ops, or similar.
• Experience with distributed systems and cloud platform understanding.
• Familiarity with ML concepts and software engineering best practices.

Aufgaben

• Develop tools and services for the ML workflow.
• Work with ML engineers to identify pain points and solutions.
• Provide training for ML teams on best practices.

Kenntnisse

Kubernetes management

Python proficiency

Communication skills

Understanding of ML concepts

Cloud services (AWS)

Ausbildung

Experience in ML infra or similar

Tools

Ray

Amazon EKS

Airflow

Terraform

Git

Jobbeschreibung

An innovative tech company in New York is seeking a member for their MLOps team. This role involves developing tools and services to enhance the ML workflow, while closely collaborating with ML engineers to identify challenges and provide effective solutions. The ideal candidate will have over 2 years of experience in ML infrastructure, strong Kubernetes and Python skills, as well as a good understanding of cloud platforms like AWS. They will also help train teams on best practices and promote efficient processes in ML product development.