AI/ML, Data Science Engineer

AI/ML, Data Science Engineer – Build the Future of Observability using Agentic AI

💼 Tech Stack & Tools

· Hands on experience with time-series algorithms, causal analytics, building model evaluations at scale and deploying in production

· Built production ready AI agents, experience in multi-model LLM fine-tuning

· Deep understanding of MLOps pipelines

🔥 What We’re Looking For

• Extensive Experience in Time-Series Analysis – Proven ability to build, deploy, and optimize time-series models for forecasting, anomaly detection, and decision-making at scale.

• Expertise in Causal Analytics – Strong understanding of causal inference techniques to drive insights and actionable recommendations from large datasets.

• Hands-on with Large-Scale Data – Experience working with high-dimensional, large-scale structured and unstructured datasets in production.

• MLOps & Model Lifecycle Management – Deep understanding of MLOps best practices, including model training, evaluation, deployment, monitoring, and continuous improvement.

• LLM Fine-Tuning & Distillation – Experience fine-tuning, distilling, or optimizing multi-modal LLMs for efficiency and accuracy in production applications.

• Strong Programming Skills – Proficiency in Python and ML-related libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.), along with experience in distributed computing frameworks (Spark, Dask, Ray).

• Production-Grade ML Systems – Track record of developing robust, scalable ML pipelines and integrating models into the production environment.

* Passion for AI and leveraging cutting-edge technologie

* Someone who is curious and think differently to challenge inefficiencies in the status quo

* A problem-solver mindset who loves building from the ground up