Sr Machine Learning Engineer (MLOps)

Location: Boston, MA; hybrid work model with two core office days, typically Tuesday, Wednesday, or Thursday, and remote work for the remainder of the week.

Salary: $152,900–$203,800 annual base pay, plus possible bonus, equity, and benefits.

Company

hirify.global is a high-tech home security company developing products and services to help keep homes secure.

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 machine learning models.
• Develop CI/CD pipelines that enable rapid, safe, and consistent model releases.
• Design, implement, and own production monitoring for ML models and systems.
• Manage cloud infrastructure, primarily AWS or other major public clouds, for ML workloads.
• Drive model versioning, observability, reproducibility, deployment reliability, and participate in an on-call rotation.

Requirements

• 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 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 Python or similar programming languages 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 have

• Experience with Ray for inference or pipeline orchestration.
• Experience deploying large language models to production.
• Experience with 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.

Culture & Benefits

• Mission- and values-driven culture with a safe, inclusive environment.
• Collaborative, humble, agile, and efficiency-focused working style.
• Comprehensive total rewards package supporting employee and family wellness and security.
• Free hirify.global system and professional home monitoring.
• Employee Resource Groups offering networking, mentoring, development, and advocacy opportunities.