Gen AI Engineer - Audio / Video
AVE Promagne · Bengaluru · onsite · Posted 49d ago
Undisclosed3–8 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
What you'll do
- Real-time clinical document generation - turn a live consultation into a structured, clinically accurate document while the clinician is still in the room. Sub-second latency, zero tolerance for hallucination.
- Fine-tuning special-purpose models -LoRA, PEFT, SFT and preference alignment, optimized for highthroughput serving. Dataset design through to production. This is where we invest in going deep.
- Speech-to-text and audio pipelines -real clinical audio: multiple speakers, accents, noise, and Swedish and German medical vocabulary no off-the-shelf model has seen.
- Medical NER and structured extraction -medications, dosages, diagnoses, procedures and temporal relationships pulled out of free text, reliable enough to write into a patient record.
- Evaluation pipelines -in healthcare, "it looks good" is not a metric. Golden datasets, automated judges, clinician-in-the-loop review, and the monitoring that catches regressions before a clinic does.
- Automated booking and scheduling -agentic systems that handle real patient interactions end to end, with real-world consequences when they go wrong.
- Data and deployment -curate clinical datasets to a training-ready standard, and take systems from experiment to monitored, production-grade services clinicians rely on at scale. You won't do all of this at once, but over time you'll touch most of it.
What we're looking for
- Bachelor's in Computer Science, Engineering, or a related field.
- 3+ years in AI/ML, with a focus on applied and Generative AI systems.
- Strong hands-on experience with LLMs, prompt engineering, and structured outputs.
- Hands-on with speech-to-text and audio-processing pipelines.
- Proficient in Python (pandas, NumPy, ML/AI libraries) and SQL.
- Familiar with cloud AI services, preferably AWS (S3, SageMaker, Bedrock).
- Understanding of LLMOps / MLOps: evaluation, monitoring, deployment, and iteration.
Sourced from naukri
Skills
Aws SagemakerBedrockFine Tuningcloud aiai servicesMLOpsamazon web servicesai engineerLLMOpsclinicLoraLarge Language Models (LLMs)AWS S3Audio ProcessingdeploymentDocument generationPythonHealthcarePatient RecordcloudSQLPandasNumpyGenerative AiArtificial IntelligenceMachine Learning