Senior Machine Learning Engineer (MLOps)

TL;DR

Senior Machine Learning Engineer (MLOps): Drives the development and deployment of ML models, optimizing ML workflows, and ensuring scalable, reliable, and secure infrastructure. Focus on architecting and owning scalable ML model serving systems, developing CI/CD pipelines for models, and managing cloud infrastructure, especially for LLM applications.

Location: Hybrid in Boston, MA (expected to be in office 2-3 days a week).

Salary: $152,800–$224,100

Company

hirify.global is a leading innovator in the home security industry, dedicated to making every home a safe home with user-centric security solutions.

What you will do

• 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 releases.
• Design, implement, and own comprehensive production monitoring for ML models/systems.
• Manage cloud infrastructure, primarily in AWS, to support ML workloads.
• Drive best practices in model versioning, observability, reproducibility, and deployment reliability.

Requirements

• 5+ years of experience in software engineering, data engineering, or a related field, with 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.
• Experience with LLM application development, including prompt engineering and evaluation.
• Must be able to work in a hybrid model from Boston, MA, with 2-3 days in the office.

Nice to have

• Experience with Ray for inference or pipeline orchestration.
• Hands-on experience with deploying large language models (LLMs) to production, including frameworks such as vLLM.
• 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.

Culture & Benefits

• A mission- and values-driven culture (Customer Obsessed, Aim High, No Ego, One Team, Lift As We Climb, Lean & Nimble).
• Comprehensive total rewards package that supports wellness and provides security for employees and their families.
• Free hirify.global system and professional monitoring for your home.
• Employee Resource Groups (ERGs) that bring people together, provide opportunities to network, mentor and develop, and advocate for change.