Ml Job At Netflix

Netflix; Lansing (MI); On-site; USD 28,000 - 55,000; Full time

Job summary

Netflix in Lansing, MI is seeking an Engineering Manager to lead a cross-functional team responsible for scalable ML infrastructure and model serving. The role focuses on delivering reliable, high-performance systems that power a wide range of Netflix features and experiences.

You will work closely with AI, data, and software engineering teams to accelerate deployment of large-scale ML workloads, mentor engineers, and set architectural direction that aligns with product goals.

Qualifications

• 3+ years of engineering management experience.
• Experience building high-traffic distributed systems and ML infrastructure.
• Ability to set and uphold high architectural standards and guide the team.

Responsibilities

• Lead a team responsible for building high-traffic distributed infrastructure to support large-scale ML models.
• Collaborate cross-functionally with engineering, product, AI, and data teams.
• Drive architectural vision and scale ML serving for broad user impact.

Skills

Engineering leadership

Cross-functional collaboration

Communication

Mentoring

Education

BS/MS in Software Engineering or related field

Tools

AWS

Azure

GCP

Java

Job description

Job Responsibilities: Engineering Manager Salary: $20-$40 Hour Company: Netflix Location: Lansing, USA Educational Requirements: Bachelor Degree

Full Job Description:- The Open door The Buyer Model Process and Serving Establishments group gives the establishment to display calculation, surmising, and serving for all ML/man-made intelligence development across the different Shopper ML spaces. The group is answerable for fostering all the structure blocks expected to run ML models at scale. These structure blocks incorporate a model serving stage, an occasion-driven model process system, a figure coordination motor, and some more. We are searching for an accomplished design pioneer for this area, which is a focal point of our business. You will be profoundly cross-utilitarian in cooperating with other designing, item executives, AI, and information groups to take Netflix's ML/man-made intelligence drives to a higher level. To find success in this job, you want serious areas of strength for a foundation and an enthusiasm for building versatile, strong frameworks that empower and speed up our capacity to apply enormous and complex ML models across an extensive variety of Buyer spaces.

Least Work Capabilities

• 3+ long periods of design administration experience
• Experience driving a group liable for building high-traffic circulated frameworks and ML foundation to help huge scope ML models with an immediate effect on the client experience
• Solid specialized insight and can go about as a valid specialized consultant to the group, set and uphold a top-notch bar for code and framework plan, and be a guide for the group
• A history of recruiting and developing different, exceptionally skilled tenured designs profound into their professions to expand their effect
• Fantastic at discussing setting with the group, partners, accomplices, and initiative, giving and getting criticism, encouraging groundbreaking thoughts, and engaging others without micromanagement
• Enthusiasm for deciphering the requirements of ML specialists into foundation contributions with an eye toward mechanized and self-serve abilities
• Exhibited capacity to create, drive, and execute a specialized vision and guide
• Open to dealing with a greater part of the remote group with accomplices dispersed across (US) geologies and time regions

Favored Capabilities

• BS/MS in Software engineering, Applied Math, Designing, or a connected field
• 3+ long periods of programming experience
• Experience constructing high-scale administrations on a public cloud like AWS, Purplish Blue, or GCP and OK with Java
• Constructed ML foundation contributions for ML Analysts, Information Researchers, and other ML specialists

At Netflix, we cautiously consider an extensive variety of pay elements to decide your top of the market. We depend on market pointers to decide on pay and think about your particular work, abilities, and experience to take care of business. These contemplations can make your remuneration fluctuate and will likewise be reliant upon your area.