Senior Staff Applied ML Engineer
Not sure if you're a good fit?
Upload your resume and TixelJobs AI will compare it against Senior Staff Applied ML Engineer at Kaseya. Get a match score, missing keywords, and improvement tips before you apply.
Free preview · Your resume stays private
About the Role
About Kaseya
Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success.
Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide.
Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike.
At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar.
We’re hiring Applied ML Engineers to partner with multiple product teams to extract insights from data and build AI-powered features and automated workflows across the product suite.
In this role, you will both:
- Enable product teams: teach, coach, and guide them on data and ML best practices
- Lead by example: do complex data analysis and ML modeling, architecture, and implementation work as needed to accelerate teams while mentoring more junior data/ML folks.
You’ll own the data analysis, ML modeling, and workflow logic that let AI understand user requests, enrich and route them, suggest actions, and in some cases fully automate resolution.
What You’ll Do
Data & ML Modeling
- Explore and analyze data using Python, pandas, and PySpark (or similar tools).
- Use matrix factorization, clustering, dimensionality reduction, and related techniques to understand and prepare data for modeling, and to identify and label latent factors (e.g., user behavior patterns, content/topic clusters, expertise dimensions).
- Create, tune, and productionize ML models for:
- Categorization / classification
- Recommendations and similarity
Ready to apply?
This job is active. Apply now to get in early.