Ai Ml Engineer

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 strong engineering team