Senior ML Engineer

New

Smart WorkingMachine learning

Listing location: India / Chandigarh / New Delhi / Hyderabad / Pune / Indore / Bangalore; Workplace type: RemotePart-TimeSenior

Salary not disclosed

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Job Details

Required Skills: DockerApache AirflowKubernetesMachine LearningMLOpsGenerative AI

Have a proven track record at the intersection of Machine Learning, MLOps, and Platform/Backend Engineering.
Understand evaluation metrics for generative AI, LLMs, and/or speech models, including Precision, Recall, F1, WER/CER, groundedness, and hallucination rates.
Bring hands-on containerisation experience with Docker and Kubernetes.
Have experience with modern orchestration frameworks.
Have experience building observable ML systems with logging and monitoring.
Have experience with strict cost-attribution tracking.
Be familiar with data provenance and compliance standards.
Be familiar with fail-safe mechanisms for sensitive data and AI outputs.

Refactor and upgrade NLP, generative AI, and transcription models into standardised, production-ready modular contracts.
Engineer resilient ML workflows using DAG-based orchestration tools such as Argo Workflows and Airflow.
Implement retry logic, error handling, and repeatable execution across ML workflows.
Define, automate, and maintain ML evaluation pipelines using golden datasets.
Check that new models meet baseline quality and performance thresholds before release.
Build tracking mechanisms for model, prompt, and input data provenance to support auditability and reproducibility.
Build infrastructure for shadow testing and A/B testing on live traffic.
Implement fallback and kill-switch mechanisms for safe deployment.
Build feedback pipelines to capture human reviews and corrections for training datasets.
Integrate third-party AI APIs and manage adapter interfaces; track compute costs, token usage, and latency.

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