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Staff Machine Learning Engineer

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Staff Machine Learning Engineer in USA new

  • SimpliSafe
  • Full time
  • Email
  • Boston, MA

Responsibilities

  • Define the technical vision, architecture, and multi-quarter roadmap for the ML data and training platform.
  • Architect scalable data and feature pipelines that produce reliable, versioned training datasets.
  • Build distributed training infrastructure for classical ML, deep learning, and LLM fine-tuning, including GPU scheduling and utilization.
  • Own experiment tracking, model registry, dataset lineage, and model lineage to ensure reproducibility.
  • Develop CI/CD and automation for training pipelines.
  • Partner with data science, data engineering, product, and security leaders to align platform priorities and execute ambiguous initiatives.
  • Set organization-wide standards for data versioning, training reproducibility, and data governance.
  • Lead build-versus-buy evaluations and make technology decisions involving ML tooling, cloud services, and frameworks.
  • Improve reliability and cost efficiency of AWS data and training workloads through capacity planning and compute and GPU optimization.
  • Mentor and grow engineers through design reviews, code reviews, and technical coaching.
  • Participate in on-call rotations and lead postmortems for critical platform incidents.

Requirements

  • 8+ years of experience in software engineering, data engineering, or a related field, including at least 4 years focused on ML infrastructure or MLOps.
  • Proven technical leadership designing and shipping ML training platforms, data platforms, or large-scale distributed systems end to end.
  • Experience leading cross-team initiatives without direct authority.
  • 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 such as Terraform or CloudFormation.
  • Strong Python proficiency and hands-on experience with machine learning frameworks such as PyTorch or TensorFlow.
  • Hands-on experience with distributed training and large-scale data processing such as Ray, Spark, or PyTorch Distributed.
  • Deep understanding of experiment tracking, model registries, and data and model versioning tools such as MLflow, Weights & Biases, or DVC.
  • Excellent written and verbal communication skills, including technical design documentation and stakeholder influence.
  • Preferred experience handling PII data; using Airflow, Kubeflow, Flyte, or Step Functions; working with feature stores or data lakehouses; building pipelines for video, image, or audio datasets; using Kafka or Kinesis; and applying cloud security, IAM, data privacy, and compliance practices.

Benefits

  • Hybrid work model with two core in-office days, typically Tuesday, Wednesday, or Thursday, and flexibility to work from home for the remainder of the week.
  • Comprehensive total rewards package with medical, retirement, lifestyle, wellness, and family-support benefits.
  • Free SimpliSafe system and professional monitoring for the employee’s home.
  • Employee Resource Groups offering networking, mentoring, development, and advocacy opportunities.
  • Mission- and values-driven culture with an inclusive and supportive work environment.

Salary: $184k - $245k/yr

SimpliSafe

SimpliSafe builds DIY wireless home security systems—sensors, smart locks, and cameras—sold direct to consumers with optional 24/7 professional monitoring on a subscription basis. Founded in 2006 and headquartered in Boston, it is privately held and majority-owned by Hellman & Friedman. Its syste...

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