Staff Machine Learning Engineer

About SimpliSafe

Were a high-tech home security company thats passionate about protecting the life youve built and our mission of keeping Every Home Secure. And weve created a culture here that cares just as deeply about the career youre building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We dont just want you to work here. We want you to grow and thrive here.

Were embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state-of-the-art office on two core days typically Tuesday Wednesday or Thursday working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done.

Why are we hiring

Well were growing and thriving. So we need smart talented and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure.

About the Role
We are looking for a Staff Machine Learning Engineer to serve as the technical leader for ourML data and training this role you will set the technical direction for how SimpliSafeprepares data trains fine-tunes and tracks machine learning models including large languagemodels. You will own the architecture of our data and training infrastructure drive multi-quarterinitiatives across teams and raise the engineering bar through design reviews mentorship andstandards. If you want to shape how ML models get built at scale wed love to hear from you.

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

Qualifications
8 years of experience in software engineering data engineering or a related field withat least 4 years focused on ML infrastructure or MLOps.
Proven track record of technical leadership: designing and shipping ML training platformsdata platforms or large-scale distributed systems end to end and leading cross-teaminitiatives without direct authority.
Expert-level experience with AWS or similar public clouds including compute storagenetworking and container orchestration.
Deep experience with CI/CD pipelines Docker Kubernetes and infrastructure-as-codetools (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. RaySpark PyTorch Distributed).
Deep understanding of experiment tracking model registries and data and modelversioning (e.g. MLflow Weights & Biases DVC).
Excellent written and verbal communication skills including writing technical design docsand influencing senior technical and non-technical stakeholders.

Nice to Have
Experience handling PII data
Experience with workflow orchestration tools (e.g. Airflow Kubeflow Flyte StepFunctions).
Experience with feature stores and data lakehouse technologies (e.g. Feast SageMakerFeature Store Delta Lake Iceberg).
Experience building pipelines for large unstructured datasets such as video images oraudio including labeling and curation workflows.
Experience with event-driven or streaming data architectures (e.g. Kafka Kinesis).
Knowledge of cloud security IAM data privacy and compliance best practices for MLdata and workloads.

What Values Youll Share

• 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.

What We Offer

• A mission- and values-driven culture and a safe inclusive environment where you can build grow and thrive
• A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here)
• Free SimpliSafe system and professional monitoring for your home.
• Employee Resource Groups (ERGs) that bring people together give opportunities to network mentor and develop and advocate for change.

The target annual base pay range for this role is $183500 - $244600

This target annual base pay range represents our good-faith estimate of what we expect to pay for this role. We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually. We carefully tailor individual compensation packages including base pay taking into consideration employees job-related skills experience qualifications work location and other relevant business factors.

Beyond base pay we offer a Total Rewards package that may include participation in our annual bonus program equity and other forms of compensation in addition to a full range of medical retirement and lifestyle benefits. More details can befound here.

Were committed to fair and equitable pay practices as well as pay transparency. We regularly review our programs to ensure they remain competitive and aligned with our values.

We wholeheartedly embrace and actively seek applications from all individuals no matter how they identify. We are committed to cultivating a diverse and inclusive workplace and we believe our work is enriched when we incorporate a multitude of perspectives backgrounds and experiences. We want everyone who works here to thrive and contribute to not only our mission of keeping every home secure but also to making our workplace safe and supportive for others. If a reasonable accommodation may be needed to fully participate in the job application or interview process to perform the essential functions of a position or to receive other benefits and privileges of employment please contact.