26 Sep
begig
Secunderabad
Job Role- Senior ML Engineer
Job type- Contract/Freelance
Work Mode- Remote(6-8 hours per day)
Machine Learning Engineer – Predictive Maintenance / NLP
About the Role
We are looking for a Machine Learning Engineer with strong expertise in anomaly detection, root-cause diagnosis, and NLP-based document understanding. You will develop intelligent pipelines that detect recurring machine failures, analyze unstructured technical documentation, and integrate into a SaaS-ready AI maintenance platform.
Responsibilities
- Develop ML models for anomaly detection and root-cause analysis using sensor, log, and text data.
- Leverage Neo4j knowledge graphs and RAG pipelines to map symptoms → causes → solutions.
- Process unstructured technical documentation (PDFs) and integrate with embeddings/LLM workflows.
- Optimize and calibrate ML models with OpenVINO and available datasets..
- Collaborate with backend and frontend engineers to deliver outputs via a chatbot interface.
- Work closely with stakeholders to validate detection accuracy, diagnosis, and recommendations.
Must-Have Skills
- 5–8 years total ML experience, with 3+ years in anomaly detection / unsupervised ML (sensor, IoT, or predictive maintenance).
- 2–3 years NLP experience (document parsing, embeddings, Hugging Face, LangChain/LlamaIndex).
- Solid Python programming (scikit-learn, SciPy, PyTorch/TensorFlow).
- Hands-on experience with knowledge graphs (Neo4j or similar).
- OpenVINO for model optimization and serving.
- Familiarity with vector databases (Weaviate, Pinecone, etc.).
- Cloud-based model training, ML deployment and monitoring on AWS and Azure AI Foundry.
Good-to-Have Skills
- Prior experience with Vertex AI (optional)
- Experience with calibration agents or adaptive learning workflows.
- Understanding of SaaS-ready architectures and API-first integrations.
- Ability to support basic data engineering (batch pipelines, ETL with Flask).
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