Role & responsibilities

- Design and build LLM workflows using structured outputs, tool/function calling, routing, retrieval (RAG) and controlled orchestration

- Build predictive models for classification, ranking, forecasting, anomaly detection and recommendation

- Create data pipelines, feature workflows, training/evaluation datasets, model registries and reproducible experiments

- Define offline/online evaluation, regression suites, quality thresholds and human-review processes

- Monitor model quality, drift, latency, usage and cost; diagnose and fix failures using measured feedback

- Implement safeguards against prompt injection, unsafe tool use, data leakage and unsupported model claims

- Deploy AI capabilities as versioned, documented APIs and work closely with backend, frontend, QA and security teams

- Build reusable AI foundations that serve multiple products

Preferred candidate profile

- 3 - 7 years in applied AI/ML, with production models or LLM-enabled systems

- Strong Python; hands-on with scikit-learn, PyTorch, TensorFlow or equivalent

- Production experience with LLM APIs, structured outputs, function calling, retrieval and prompt evaluation





- Solid grasp of precision, recall, calibration, drift, experiment design and error analysis

- Comfortable with SQL, event data, time-series and large analytical datasets

- Experience deploying models behind APIs with versioning and monitoring

- Good judgement on when to use rules, classical ML, LLMs or a hybrid

- Clear communicator with technical and non-technical stakeholders

Good to have

- LangGraph or similar orchestration frameworks

- Time-series forecasting, causal inference, uplift modeling, recommendations or contextual bandits

- Multimodal (image, audio, video) analysis

- AI observability/evaluation platforms, inference optimization, LLM cost management

- Experience building shared AI platforms for multiple product teams

Why Join Us

- Core technology role owning AI from build to production across multiple digital products

- Move beyond demos: ship real, measurable, production-grade AI

- Shape reusable AI foundations and future product versions

- Work across LLM systems and predictive ML with a robust engineering team

📌 Ai Ml Engineer (Noida)
🏢 Juuuno
📍 Noida