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# Sr Machine Learning Engineer

- **Company:** SimpliSafe, Inc
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $152,900.0 - $203,800.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Big Data, Cloud Computing, Cloud Computing Security, Computer Programming, Continuous Integration, Information Engineering, Distributed Systems, Apache Hadoop, Identity and Access Management, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Management of Software Versions, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Cloudformation, Event Driven Architecture, Kubernetes, Infrastructure Automation Frameworks, Apache Kafka, Machine Learning Operations, Terraform, Software Version Control, Data Pipelines, Docker
- **Published:** October 28, 2026
- **Apply:** https://www.thejobnetwork.com/job/c72a31ed-0183-4240-ae34-9e7a2a61949d/sr-machine-learning-engineer

## About the Role

* 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 (e.g., Terraform, Cloud Formation).
 * Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, 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 Have

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

## Description

We are looking for an experienced ML Infrastructure/MLOps Engineer to join our team as a Senior Machine Learning Engineer. In this role, you will drive the development and deployment of machine learning models, optimize ML workflows, and help ensure our infrastructure is scalable, reliable, and secure. If you have a passion for automation, cloud technology, and delivering high-impact solutions, we'd love to hear from you., * 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 enabling rapid, safe, and consistent model releases.
 * Design, implement, and own comprehensive production monitoring for ML models/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 your team., * Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them.
 * Aim High - Always challenging ourselves and others to raise the bar.
 * No Ego - Maintaining a "no job too small" attitude, and an open, inclusive and humble style.
 * One Team - Taking a highly collaborative approach to achieving success.
 * Lift As We Climb - Investing in developing others and helping others around us succeed.
 * Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment.