Sr Machine Learning Engineer

SimpliSafe is hiring a Senior Machine Learning Engineer to help take machine learning models from development through deployment and ongoing operations. In this hybrid role based in Boston, MA, you will focus on building and improving ML model serving, automation, and monitoring so ML systems can scale with confidence.

What you’ll do

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

What you bring

• 5+ years of experience in software engineering, data engineering, or a related field, including at least 3 years focused on MLOps or ML infrastructure.
• Deep hands-on experience with AWS (or comparable 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 and Cloud Formation.
• Proficiency in Python, along with familiarity with ML frameworks including TensorFlow and PyTorch.
• Strong understanding of the ML lifecycle, including experiment tracking, versioning, and monitoring.
• Strong communication skills for collaborating with both technical and non-technical teams.

Technologies you may work with

• AWS, Python, TensorFlow, PyTorch
• Docker, Kubernetes
• Terraform, Cloud Formation
• Ray, vLLM, Spark, Hadoop
• Kafka, Kinesis

Nice to have

• 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 (for example, Spark, Hadoop).
• Experience with event-driven or streaming architectures (for example, Kafka, Kinesis).
• Knowledge of cloud security, IAM, and compliance best practices for ML workloads.
• LLM application development experience, including prompt engineering and evaluation.

Benefits

• A mission- and values-driven culture with a safe, inclusive environment to build, grow, and thrive.
• A comprehensive total rewards package supporting wellness and providing security for SimpliSafers and their families.
• Free SimpliSafe system and professional monitoring for your home.
• Employee Resource Groups (ERGs) for networking, mentoring, development, and advocating for change.

Hybrid work model

• Hybrid model that lets teams split time between office and home.
• Teams meet in the state-of-the-art office on two core days, typically Tuesday, Wednesday, or Thursday, and choose where to work for the rest of the week.

Pay range

The target annual base pay range for this role is $152,900 - $203,800.

Values you’ll share

• Customer Obsessed
• Aim High
• No Ego
• One Team
• Lift As We Climb
• Lean & Nimble