Senior ML Engineer

1 day ago

Bengaluru, India Sarvam Full time

Sarvam AI is building the next-generation media AI engine to automate movie and OTT content creation & localization across India's diverse languages. We're seeking a Senior Machine Learning Engineer to oversee the orchestration of our end-to-end AI in Media pipeline, which combines cutting-edge models, agile workflows, and media-grade quality automation.

About the Role

This role requires in-depth expertise in speech and audio AI, agile pipeline orchestration, and scalable ML system design knowledge. The ideal candidate has a
strong track record of building and deploying production-grade ML pipelines, leading technical teams, and solving complex problems in audio/video processing and generative media
workflows.

Key Responsibilities

  • Own the design and evolution of Sarvam's Media AI pipeline by combining agent-based orchestration, scalable ML integration, and rapid experimentation.
  • Build and lead the development of production-grade ML pipelines,
    ensuring robustness, automation, and adaptability to media workflows.
  • Prototype and deploy agentic systems (
    multi-agent frameworks, LLM-driven decision engines
    , self-optimizing workflows) to automate task sequencing, error handling, and quality evaluation.
  • Drive continual improvements through prompt engineering, RAG,
    fine-tuning, and metric-driven performance monitoring
    .
  • Define pipeline-wide standards for quality, testing, fallback mechanisms, and edge-case handling.
  • Collaborate with model researchers, infra/platform teams, and product stakeholders to ensure end-to-end reliability.
  • Provide
    technical leadership and mentorship
    across the orchestration and pipeline engineering team.

Technical Expertise

  • 4-7 years of experience in ML/AI engineering
  • Hands-on expertise in Generative AI: LLMs, prompt design, and building complex agentic systems.
  • Strong proficiency in
    Python, PyTorch/TensorFlow, MCP and agent orchestration
    frameworks (LangChain, LangGraph, Langfuse, or custom DAGs).
  • Proven track record of deploying ML pipelines in production at scale with monitoring and alerts, comfortable with CUDA profiling and tensor debugging.
  • Familiarity with ASR/TTS/translation models such as Whisper, wav2vec, F5, Coqui TTS, FastSpeech, Bark, Wav2Lip, etc.
  • Experience with cloud platforms (GCP/AWS), containerised deployments (Docker/Kubernetes), and scalable inference (Triton, ONNX, Kubeflow, MLflow) is a plus.

Leadership & Soft Skills

  • Entrepreneurial spirit with hands-on experience in 0-to-1 startup phases.
  • Proven ability to lead and mentor ML teams, balancing research rigour with production needs.
  • Strong systems thinking and cross-functional coordination (models, infra, inference, QA, product).
  • Passion for keeping pace with the latest in Gen AI, LLMs, and ML engineering.
  • Experience working with media/OTT post-production pipelines is a plus.

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