Demandbase

Staff Machine Learning Engineer

Demandbase

full-time

Posted on:

Location Type: Hybrid

Location: Hyderabad • India

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Job Level

Lead

Tech Stack

AirflowCloudJavaKafkaPythonScalaSpark

About the role

  • Lead the design and development of AI/ML systems starting from problem framing, decision boundaries, and operational constraints.
  • Drive system and architecture decisions for AI and ML platforms, ensuring scalability, performance, and operational excellence.
  • Design and evolve context engineering strategies for LLM-based systems under strict context window and latency constraints.
  • Architect agent-based systems, including agent roles, interaction models, coordination strategies, and failure handling.
  • Build and operate production AI systems with ownership of reliability, latency, cost, and correctness.
  • Define evaluation frameworks for AI and agent behavior beyond offline model metrics.
  • Scale AI-assisted development and reusable AI workflows to improve engineering velocity and system quality.
  • Review and approve ML designs, guiding tradeoffs across model quality, system complexity, and business impact.
  • Mentor senior engineers and data scientists, raising standards in AI system design, ML engineering, and production readiness.
  • Partner with product and engineering leaders to translate ambiguous business problems into well-scoped, high-impact AI/ML solutions.
  • Contribute to multi-quarter technical strategy, aligning AI and ML investments with company objectives.

Requirements

  • 12+ years of experience across AI, ML, and software engineering roles.
  • Strong coding skills in Python, Scala, or Java, with a track record of production-quality systems.
  • Hands-on experience in building, evaluating, and operating LLM-powered systems in production.
  • Strong understanding of context engineering, including information prioritization, relevance, and degradation under constraints.
  • Experience designing AI workflows or agentic systems, including task decomposition, orchestration, and failure handling.
  • Deep hands-on expertise in ML system design, NLP, feature engineering, and operational ML.
  • Experience deploying AI/ML systems on at least one major cloud platform.
  • Hands-on experience with Big Data or streaming systems (e.g., Spark, Kafka, Airflow).
  • Proven ability to lead through influence, mentor engineers, and drive cross-team initiatives.
  • Strong business and product mindset, with the ability to map AI/ML solutions to measurable outcomes.
Benefits
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Applicant Tracking System Keywords

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Hard Skills & Tools
AI systems designML systems designcontext engineeringNLPfeature engineeringoperational MLPythonScalaJavaAI workflows
Soft Skills
mentoringleadershipcross-team collaborationbusiness mindsetinfluence