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Ml / Ai Data Engineer

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Tech Holding

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Location:
India

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Category:
IT - Software Development

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Contract Type:
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Salary:

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Job Description:

We are looking for a highly skilled Senior ML / Data Pipeline Engineer who can translate complex machine learning and multimodal concepts into scalable, production-ready pipelines and workflows. This role focuses on building and optimising large-scale video and multimodal data systems, enabling high-throughput ingestion, processing, and model training across distributed cloud environments.

Job Responsibility:

  • Design, deploy, and scale large-scale ML and data processing pipelines across cloud infrastructure
  • Build systems to ingest, process, and serve 250,000+ hours of multimodal data (video, audio, metadata)
  • Architect and optimize GPU-based compute environments (e.g., NVIDIA Tesla clusters) for distributed training and inference
  • Develop high-throughput backend systems for video ingestion from desktop and mobile platforms
  • Implement distributed processing workflows, including job scheduling, fault tolerance, and resource allocation
  • Design and build human-in-the-loop and automated annotation systems to ensure data quality and scalability
  • Translate ML and multimodal research into scalable, production-grade cloud architectures
  • Optimize pipelines for performance, reliability, and cost efficiency across compute, storage, and networking layers
  • Collaborate with ML, data, and engineering teams to deliver end-to-end data workflows

Requirements:

  • 5+ years of experience in data engineering, ML pipelines, or distributed systems
  • Strong experience building scalable data pipelines for large datasets (video/audio preferred)
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP)
  • Experience working with GPU-based environments and distributed computing
  • Strong programming skills in Python, Scala, or similar languages
  • Experience with data processing frameworks (Spark, Ray, Kafka, Airflow, or similar)
  • Understanding of ML workflows, training pipelines, and inference systems
  • Experience designing fault-tolerant, high-availability systems
  • Strong knowledge of data storage systems (data lakes, object storage, distributed file systems)
  • Ability to handle high-throughput, large-scale data ingestion and processing

Nice to have:

  • Experience with multimodal AI (video, audio, NLP) systems
  • Familiarity with annotation tools and data labeling workflows
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Knowledge of cost optimization strategies for large-scale cloud workloads

Additional Information:

Job Posted:
May 16, 2026

Work Type:
Remote work
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