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4.0 - 8.0 years

0 Lacs

karnataka

On-site

As a Senior Machine Learning Engineer at Sarvam AI, you will be responsible for overseeing the orchestration of the end-to-end AI in Media pipeline. Your role will involve combining cutting-edge models, agile workflows, and media-grade quality automation to automate movie and OTT content creation & localization across India's diverse languages. **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 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, including 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 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), containerized deployments (Docker/Kubernetes), and scalable inference 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 rigor with production needs. - Strong systems thinking and cross-functional coordination. - 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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