Senior Staff Applied ML Engineer

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. Overview 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: o Categorization / classification o Recommendations and similarity o Other prediction or ranking tasks that power product features AI-Powered Workflows & Features · Design and implement AI-driven ingest flows that turn unstructured inputs (tickets, emails, forms, messages, logs, etc.) into well-structured data that models and downstream systems can use. · Build workflows where AI can: o Auto-fill or suggest key fields and metadata. o Proactively ask users/customers for missing or ambiguous information (e.g., via email or messaging). o Surface similar past items or solutions to assist humans in decision-making. o Fully handle simple, repetitive “Level 1” style requests end-to-end when safe to do so. · Work closely with engineers to integrate models and workflows into production systems with proper monitoring, fallbacks, and guardrails. Cross-Team Leadership & Enablement · Work with multiple product teams to help them identify and scope AI opportunities in their areas. · Define patterns, templates, and best practices for data ingestion, feature creation, model usage, and evaluation that teams can reuse. · Serve as a trusted advisor and technical lead: o Provide design and architecture guidance on data and ML-heavy features. o Join projects to handle the most complex modeling or workflow automation pieces when teams get stuck. · Mentor and guide junior data/ML engineers and analysts: o Conduct code and model reviews. o Pair with them on tricky problems. o Help them develop good intuitions about metrics, evaluation, and operational reliability. · Help establish and socialize standards for experimentation, documentation, and responsible AI usage across teams. What You’ll Bring Core Skills · 5+ years in data science, ML engineering, or a similar applied role, with a strong record of shipping production data/ML features. · Strong Python skills and experience with pandas