Data Scientist

Company Description Fast Code AI is a Bengaluru-based R&D partner for enterprises tackling complex, production-grade AI challenges. The team focuses on areas such as video diffusion, LLM post-training on proprietary data, and robust time-series foundation models designed for real-world deployment. Fast Code AI is trusted by leading organizations including Mercedes-Benz, Bosch, Volkswagen, and Aramco for their most demanding AI problems. The company is built by researchers with frontier-lab credentials who chose to specialize in research-grade engineering for domain-specific enterprise needs. Fast Code AI maintains a principled approach and turns down projects where AI is not the right solution.

Role Description This is a full-time, on-site Data Scientist role based in Bengaluru. The Data Scientist will design, develop, and validate models for video diffusion, large language model post-training, and time-series applications on complex, domain-specific datasets. Responsibilities include exploring data, performing rigorous statistical analysis, building and iterating on machine learning pipelines, and collaborating with engineering teams to deploy solutions that perform reliably in production. The role involves close partnership with enterprise clients to understand their constraints, translate business requirements into technical specifications, and communicate findings through clear reports and visualizations. The Data Scientist is expected to experiment with new methods, evaluate when AI is or is not the appropriate tool, and contribute to internal research and reusable tooling.

Qualifications

• Strong proficiency in

Python and solid software engineering fundamentals.

• Hands‑on experience with

ML/AI frameworks such as PyTorch, TensorFlow, or similar.

• Experience with

model deployment (REST/gRPC services, batch pipelines).

• Knowledge of

MLOps tools and practices (e.g., MLflow, pipelines, monitoring).

• Experience with

cloud or on‑prem compute environments ; familiarity with containers (Docker) and orchestration (e.g., Kubernetes) is a plus.

• Solid understanding of

machine learning and deep learning concepts (training vs inference, overfitting, evaluation metrics).

• Ability to work with

data pipelines , preprocessing steps, and feature engineering outputs created by Data Scientists.

• Ability to work on-site in Bengaluru, collaborate in cross-functional teams, and communicate technical concepts clearly in spoken and written English.
• Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience.