Sr Machine Learning Engineer

SimpliSafe • Boston, MA

1d • $152,900 - $203,800 • Hybrid

About The Position

SimpliSafe is seeking an experienced ML Infrastructure/MLOps Engineer to join its team as a Senior Machine Learning Engineer. The role drives the development and deployment of machine learning models, optimizes ML workflows, and helps ensure the infrastructure is scalable, reliable, and secure. It focuses on automating and operating machine learning systems, using cloud technology to deliver high-impact solutions. The position partners with data scientists, engineers, and other stakeholders to operationalize models and supports real-time and batch use cases. It also participates in an on-call rotation as a first responder for software owned by the team.

SimpliSafe uses a hybrid work model. Employees are expected to work together in the office on two core days, typically Tuesday, Wednesday, or Thursday, and may choose where they work the remainder of the week.

Requirements

• At least 5 years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure.
• Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks.
• Hands-on experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools such as Terraform or CloudFormation.
• Proficiency in programming languages such as Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring.
• Strong communication skills for partnering with cross-functional technical and non-technical teams.

Nice To Haves

• Experience with Ray for inference or pipeline orchestration.
• Hands-on experience deploying large language models (LLMs) to production.
• Experience with frameworks such as vLLM.
• Experience with distributed systems and big data technologies such as Spark or Hadoop.
• Experience with event-driven or streaming architectures such as Kafka or Kinesis.
• Knowledge of cloud security, IAM, and compliance best practices for ML workloads.
• LLM application development, including prompt engineering and evaluation.

Responsibilities

• Lead the architecture, deployment, and optimization of scalable ML model-serving systems for real-time and batch use cases.
• Collaborate with data scientists, engineers, and stakeholders to operationalize ML models.
• Develop CI/CD pipelines for ML models to enable rapid, safe, and consistent model releases.
• Design, implement, and own comprehensive production monitoring for ML models and systems.
• Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads.
• Drive best practices in model versioning, observability, reproducibility, and deployment reliability.
• Serve in an on-call rotation as a first responder for software owned by the team.

Benefits

• A mission- and values-driven culture and a safe, inclusive environment to build, grow, and thrive.
• A comprehensive total rewards package supporting wellness and providing security for employees and their families.
• Free SimpliSafe system and professional monitoring for the employee's home.
• Employee Resource Groups that provide opportunities to network, mentor, develop, and advocate for change.
• The total rewards package may include participation in an annual bonus program, equity, and other forms of compensation, in addition to medical, retirement, and lifestyle benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed