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Machine Learning Engineer II

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Machine Learning Engineer II in Others

  • Demandbase
  • Full time
  • Email
  • Hyderābād, India

Responsibilities

  • Design, develop, and productionize machine learning and GenAI solutions for Company and Domain intelligence.
  • Build data and feature pipelines for structured, semi-structured, and unstructured first-party and third-party data.
  • Develop LLM applications using RAG, semantic retrieval, tool and function calling, agentic workflows, enterprise APIs, and internal data sources.
  • Create reusable AI services, APIs, orchestration components, evaluation datasets, automated evaluation frameworks, and feedback loops.
  • Define quality metrics and acceptance criteria covering accuracy, relevance, grounding, latency, reliability, and cost.
  • Analyze production failures and improve data, models, prompts, retrieval strategies, and agent behavior.
  • Apply guardrails, grounding, monitoring, and data-quality controls to improve system reliability.
  • Own features end to end from design and evaluation through deployment, monitoring, and support.
  • Operate cloud-native AI services and improve quality, reliability, latency, scalability, and cost.
  • Apply engineering practices involving distributed systems, concurrency, performance, testing, debugging, and code reviews.

Requirements

  • 5–7 years of experience in Machine Learning Engineering, Applied ML, Data Science Engineering, or related areas.
  • Strong Python programming and software engineering fundamentals; Scala experience is a plus.
  • Hands-on experience building and productionizing machine learning models or ML-driven applications.
  • Experience with Generative AI and LLM technologies, including LLM APIs or open-source models, embeddings, prompt engineering, and RAG.
  • Strong understanding of model training, feature engineering, model evaluation, experimentation, and inference.
  • Experience with NLP, transformers, embeddings, or other techniques for unstructured data.
  • Strong SQL knowledge and experience working with large datasets.
  • Working knowledge of at least one cloud platform: AWS, GCP, or Azure.
  • Experience with Spark, Kafka, Airflow, or similar large-scale data-processing technologies is preferred.
  • Experience with entity resolution, record linkage, classification, data mining, data enrichment, large-scale first-party or third-party datasets, or heterogeneous enterprise data is preferred.
  • Experience with Kubernetes, Docker, CI/CD, ML deployment workflows, MLOps/LLMOps, experiment tracking, model and prompt versioning, and production ML monitoring is preferred.

Benefits

  • Group medical, personal accident, and term life insurance.
  • Preventive dental, vision, and OPD healthcare coverage.
  • Mental health support and a fitness benefit.
  • Car lease policy and gratuity for long-term financial well-being.
  • The company promotes diversity, equity, inclusion, and equal opportunity.

Demandbase

Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandb...

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