Sr Software Engineer, MLOps

Vivint, Inc.
Seattle, WA, United States
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Compensation
$150,000.0 - $180,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Computer Vision Cloud Engineering Continuous Integration Data Validation Python (Programming Language) Machine Learning Recommender Systems Azure Machine Learning Software Engineering Management of Software Versions
+8 more
Large Language Models Git AI Platforms Kubernetes Information Technology Low Latency Google Cloud Functions Machine Learning Operations

Requirements

  • Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering; or

  • Master’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering

  • Experience building production ML platforms, model serving systems, or MLOps workflows

  • Strong Python and cloud engineering skills

  • Experience with CI/CD, Git, infrastructure-as-code, and production monitoring

  • Familiarity with model registry, feature/data versioning (DVC) [CH1] , validation, deployment, rollback, and observability

  • Ability to communicate tradeoffs clearly across engineering, data science, and product teams

Preferred Qualifications:

  • Experience with GCP/AWS, Cloud Run, Kubernetes, Vertex AI, SageMaker, MLflow, or equivalent tools

  • Experience with AI services for computer vision, LLMs, multimodal models, or recommendation systems

  • Experience with data validation, dataset versioning, feature stores, or model quality monitoring

  • Experience optimizing cost, latency, reliability, and operational readiness for AI systems

  • Experience with IoT, edge AI, smart home, or distributed device environments

Benefits & conditions

Learn about the Vivint Culture and why it’s a great place to grow your career!

Here are some highlighted perks you should ask us about:

  • Paid holidays and flexible paid time away

  • Employee/Friends/Family Discounts

  • Medical/dental/vision/life coverage & 24/7 Medical Hotline

  • 401(k) + Employer Match

  • Employee Resource Groups

Job Functions:

Position requires in-office presence in Seattle, WA on a hybrid schedule for Monday, Tuesday, Wednesday, and Thursday with a work from home day on Friday. The position will start remote and then will move into the hybrid schedule.

The base salary range for this position is: $150K to $180K* *The base salary range above represents the low and high end of the salary range for this position. Actual salaries will vary based on several factors including but not limited to location, experience, and performance. The range listed is just one component of the total compensation package for employees. Other rewards may include annual bonus, short- and long-term incentives, and program-specific awards. In addition the position may be eligible to participate in the benefits program which include, but are not limited to, medical, vision, dental, 401K, and flexible spending accounts.

About the company

Welcome to the intersection of energy and home services. At NRG, we’re driven by our passion to create a smarter, cleaner and more connected future.

Vivint Smart Home, an NRG owned company, is a leading smart home company in the United States, dedicated to redefining the home experience with intelligent products and services. We find purpose in proactively protecting and keeping our customers connected to home, no matter where they are. Join the Smart Home team to create smarter, safer and more sustainable homes.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · WWC 2022

5:48 min

Balancing delivery latency with stream reliability and scale

Phil Cluff · LIVE

5:28 min

Defining MLOps and its role in production systems

Hauke Brammer · WWC 2023

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

Videos

See all

Related articles

See all