Job Description

Skills
Skill


Minimum Qualification


No data available

Key Responsibilities

Production-Grade Python:

Write clean, modular, and efficient Python code. You will refactor research scripts into production-ready software (Classes, APIs, Logging).

Model Training & Debugging:

Train Deep Learning models using

PyTorch/TensorFlow

. You must know how to debug a model that isn't learning (e.g., analyzing loss curves, adjusting learning rates, fixing vanishing gradients).

Data Engineering:

Write efficient scripts (Pandas/NumPy) to clean, normalize, and pipeline complex vehicle data.

Deployment:

Wrap your models in REST APIs (

FastAPI/Flask

) and ensure they run efficiently in a Docker container.

Growth:

Learn Semantic Web technologies (RDF, SPARQL) on the job to help us build the next generation of Neuro-symbolic AI.

Must-Have Skills

Python Mastery:

2+ years of coding. You understand

OOP

(Classes/Inheritance),

Decorators

,

Generators

, and how to write memory-efficient code.

Deep Learning Frameworks:

Hands-on experience with

PyTorch

or

TensorFlow

. You can write a custom training loop from scratch.

Problem Solving:

You can look at raw data and determine the right algorithmic approach (Classification vs. Regression vs. Clustering).

Nice to Have

Experience with Graph Databases (Neo4j). Familiarity with Cloud platforms (AWS/Azure). * Understanding of Transformers or LLM architectures