Sr Machine Learning Engineer

Description

The company builds high-tech home security products and is growing quickly. The team is hiring a senior engineer to help move machine learning models into production and keep the infrastructure behind them scalable, reliable and secure.

The team looks for people who enjoy automation and cloud technology, and who work with customer focus, high standards, humility, collaboration, a drive to develop others, and agility in unclear situations.

Responsibilities

• Design and run scalable model serving systems for both real-time and batch workloads.
• Work with data scientists, engineers and business stakeholders to get models running in production.
• Build CI/CD pipelines so ML models can be released quickly, safely and consistently.
• Build and maintain thorough production monitoring for ML models and the systems around them.
• Manage cloud infrastructure supporting ML work, mainly on AWS or another major public cloud.
• Champion good practice in model versioning, observability, reproducibility and release reliability.
• Take part in an on-call rotation as the first responder for software your team owns.

Requirements

• 5+ years in software engineering, data engineering or a related field, with at least 3 years in MLOps or ML infrastructure.
• Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration and observability tools.
• Hands-on work with CI/CD, Docker, Kubernetes and infrastructure-as-code tools such as Terraform or CloudFormation.
• Strong Python skills and familiarity with ML frameworks such as TensorFlow or PyTorch.
• Solid grasp of ML lifecycle management, including experiment tracking, versioning and monitoring.
• Clear communication with both technical and non-technical colleagues.
• Experience using Ray for inference or pipeline orchestration.
• Hands-on experience deploying large language models to production.
• Experience with frameworks such as vLLM is a plus.
• Experience with distributed systems and big data tools such as Spark or Hadoop.
• Experience with event-driven or streaming systems such as Kafka or Kinesis.
• Knowledge of cloud security, IAM and compliance practice for ML workloads.
• Experience building LLM applications, including prompt engineering and evaluation.

Conditions

Hybrid setup: be in the office on two core days, usually Tuesday, Wednesday or Thursday, and choose where you work for the rest of the week.

Target annual base pay is $152,900 to $203,800.

Pay is based on market data and adjusted each year, with individual offers reflecting skills, experience, qualifications, work location and other business factors.

The company is committed to fair, equitable and transparent pay and reviews its programs regularly.

Benefits

• A culture built on shared values, with a safe and inclusive workplace where you can build your career.
• Comprehensive total rewards supporting wellness and financial security for employees and their families.
• A free home security system from the company, plus professional monitoring for your home.
• Employee resource groups for networking, mentoring, development and advocacy.
• Possible participation in the annual bonus program, equity and other compensation, plus medical, retirement and lifestyle benefits.