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Senior Staff Applied ML Engineer

1 day, 13 hours ago
India
Full-time
Lead
Machine Learning Engineer
Software Development
Apache Spark Feature Engineering Kubeflow LLM Machine Learning Microservices MLflow MLOps Pandas Python PyTorch SQL Vertex AI
Apply Now
Kaseya

Kaseya

Kaseya provides integrated IT management and security solutions for MSPs and SMBs, enabling centralized IT operations, remote management, cybersecurity, and automation.

IT Services
1K-5K
Founded 2000
$567M raised
View All Jobs 46

Description

  • Enable product teams by teaching, coaching, and guiding them on data and ML best practices.
  • Lead complex data analysis, ML modeling, architecture, and implementation work to accelerate teams.
  • Own data analysis, ML modeling, and workflow logic for AI-assisted request understanding, enrichment, routing, and resolution.
  • Explore and analyze data using Python, pandas, and PySpark or similar tools.
  • Use matrix factorization, clustering, dimensionality reduction, and related methods to prepare data and identify latent factors.
  • Create, tune, and productionize ML models for categorization, recommendations, similarity, prediction, and ranking tasks.
  • Design and implement AI-driven ingest flows that convert unstructured inputs into structured data.
  • Build workflows that auto-fill fields, request missing information, surface similar past cases, and resolve simple requests end-to-end when safe.
  • Work closely with engineers to integrate models into production systems with monitoring, fallbacks, and guardrails.
  • Mentor junior data/ML engineers and analysts through code reviews, model reviews, and pair work.

Requirements

  • 5+ years of experience 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 for data analysis.
  • Experience with PySpark or other distributed data processing frameworks.
  • Solid understanding of ML fundamentals, including supervised learning and classification models.
  • Experience with matrix factorization, embeddings, or latent factor models.
  • Experience with feature engineering and model evaluation using offline metrics and online experiments.
  • Proficiency with PyTorch or a similar deep learning framework and related ML tooling.
  • Strong SQL skills and experience with modern data warehouses or data lakes.
  • Comfort working with APIs, microservices, and production integration of ML models, including performance and reliability considerations.
  • Experience serving as a technical lead or senior individual contributor across multiple teams or projects.
  • Experience with LLMs and language-centric workflows such as RAG, prompt engineering, fine-tuning, and tool or agent orchestration (nice to have).
  • Experience building agent-assist features or automated workflows in operational or customer-facing products (nice to have).
  • Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex, plus production model monitoring (nice to have).
  • Prior experience in a platform or enablement role supporting many product teams with shared data and ML capabilities (nice to have).

Benefits

  • Backed by Insight Venture Partners.
  • Equal employment opportunity regardless of protected characteristics.

Interested in this position?

Apply directly on the company website

Apply Now

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