Staff ML Platform Architect

Innovative Signal Analysis, Inc.; Boston (MA); Hybrid; USD 184,000 - 245,000; Full time

Benefits offered by this job

Free SimpliSafe system

Total rewards package

Employee Resource Groups (ERGs)

Job summary

SimpliSafe is seeking a Staff Machine Learning Engineer to lead the ML data and training platform, shaping the technical direction for data prep, training, fine-tuning, and model tracking. You will design scalable pipelines, supervise infrastructure, and guide cross-functional teams in building reliable, reproducible ML workflows.

The role emphasizes leading multi-quarter initiatives, driving CI/CD for training, and ensuring governance and cost efficiency on AWS.

Qualifications

• 8+ years of experience in software engineering, data engineering, or a related field, with at least 4 years focused on ML infrastructure or MLOps.
• Proven track record of technical leadership: designing and shipping ML training platforms, data platforms, or large-scale distributed systems end to end.
• Expert-level experience with AWS or similar public clouds, including compute, storage, networking, and container orchestration.
• Deep experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Strong proficiency in Python, and hands-on experience with machine learning frameworks (e.g., PyTorch, TensorFlow).
• Hands-on experience with distributed training and large-scale data processing (e.g., Ray, Spark, PyTorch Distributed).
• Deep understanding of experiment tracking, model registries, and data and model versioning (e.g., MLflow, Weights & Biases, DVC).
• Excellent written and verbal communication skills, including writing technical design docs and influencing senior technical and non-technical stakeholders.

Responsibilities

• Define and own the technical vision, architecture, and multi-quarter roadmap for SimpliSafe's ML data and training platform.
• Architect and lead the delivery of scalable data and feature pipelines that produce reliable, versioned training datasets.
• Build and evolve distributed training infrastructure for classical ML, deep learning, and LLM fine-tuning, including efficient GPU scheduling and utilization.
• Own the experimentation stack, including experiment tracking, model registry, and dataset and model lineage, so that every model is reproducible.
• Develop CI/CD and automation for training pipelines, enabling data scientists to go from idea to trained, validated model quickly and safely.
• Partner with data science, data engineering, product, and security leaders to align the platform with business priorities and turn ambiguous problems into clear, executable plans.
• Set org-wide standards and paved paths for data versioning, training reproducibility, and data governance, and drive their adoption across teams.
• Lead build-vs-buy evaluations and make durable technology decisions on ML tooling, cloud services, and frameworks.
• Drive reliability and cost efficiency of training and data workloads in AWS, including capacity planning and compute/GPU cost optimization.
• Mentor and grow senior and mid-level engineers through design reviews, code reviews, and technical coaching; act as a force multiplier for the team.
• Participate in the team's on-call rotation for platform services the team owns, and lead postmortems for critical incidents.

Skills

AWS

Python

CI/CD

Docker

Kubernetes

ML infra

Distributed systems

Leadership

Education

Bachelor's/Master's in CS/Math/CE

Tools

Terraform

CloudFormation

Airflow

Kubeflow

Job description

SimpliSafe is seeking a Staff Machine Learning Engineer to lead the ML data and training platform, shaping the technical direction for data prep, training, fine-tuning, and model tracking. You will design scalable pipelines, supervise infrastructure, and guide cross-functional teams in building reliable, reproducible ML workflows.

The role emphasizes leading multi-quarter initiatives, driving CI/CD for training, and ensuring governance and cost efficiency on AWS.