Sr Machine Learning Engineer

Why are we hiring?

Well, we're 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 an experienced ML Infrastructure/MLOps Engineer to join our team as a Senior Machine Learning Engineer. In this role, you will drive the development and deployment of machine learning models, optimize ML workflows, and help ensure our infrastructure is scalable, reliable, and secure. If you have a passion for automation, cloud technology, and delivering high-impact solutions, we'd love to hear from you.

Responsibilities

• 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 model releases.
• Design, implement, and own comprehensive production monitoring for ML models/systems.
• Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads.
• Drive best practices in model versioning, observability, reproducibility, and deployment reliability
• Serve in an on-call rotation as a first responder for software owned by your team.

Qualifications

• 5+ years of experience in software engineering, data engineering, or a related field, with 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 (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.
• Strong communication skills for partnering with cross-functional technical and non-technical teams.

Nice to Have

• Experience with Ray for inference, or pipeline orchestration
• Hands-on experience with deploying large language models (LLMs) to production.
• Experience with frameworks such as vLLM is a plus.
• 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.
• LLM application development, including prompt engineering and evaluation.

What Values You'll 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 $152,900 - $203,800

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 be found here.
• We're 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.