AI Developer / Data Scientist

Awign; Bengaluru Urban; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Awign in Bengaluru, India is seeking an AI Engineer / Data Scientist to design, develop, and deploy cutting-edge AI models, contributing to innovation and business value. This hands-on role requires expertise in building scalable ML/AI systems and collaborating with cross-functional teams.

You will develop end-to-end ML pipelines, fine-tune large models, and deploy via APIs on cloud platforms, with a focus on MLOps, Transformers, and NLP.

Qualifications

• Hands-on experience building and deploying ML/DL models at scale.
• Strong Python, Pandas, NumPy, and ML libraries.
• Experience with Transformers, LLMs, or NLP models.
• Familiar with ML pipelines and MLOps practices.

Responsibilities

• Develop, train, and evaluate advanced AI/ML models for applications including classification, prediction, NLP, computer vision, and Generative AI.
• Collaborate closely with data scientists, product managers, and fellow engineers to conceptualize and build impactful AI-powered features and solutions.
• Construct and refine robust end-to-end ML pipelines, from efficient data ingestion to seamless model deployment in production environments (MLOps Pipelines).
• Apply state-of-the-art techniques, including transfer learning, reinforcement learning, and the fine-tuning of pre-trained models, with a strong focus on LLMs or CNNs.

Skills

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Transformers

LLMs

NLP

ML pipelines

Flask

FastAPI

Docker

AWS SageMaker

GCP Vertex AI

SQL

ETL

Data preprocessing

Feature engineering

Model evaluation

Collaboration

Education

Bachelor's or Master's in CS/AI

Tools

Docker

Flask

FastAPI

AWS SageMaker

Vertex AI

Cloud Run

Job description

Bangalore North, India | Posted on 08/25/2025

Job Summary: We're seeking a passionate and skilled AI Engineer / Data Scientist to join our rapidly growing AI & Data Science team. In this pivotal role, you'll be at the forefront of designing, developing, and deploying cutting‑edge AI models and systems, directly contributing to innovation and business value. This hands‑on position requires deep expertise in building and scaling machine learning and deep learning models, with a collaborative spirit to work across various teams.

Key Responsibilities:

• Develop, train, and evaluate advanced AI/ML models for applications including classification, prediction, NLP, computer vision, and Generative AI.
• Collaborate closely with data scientists, product managers, and fellow engineers to conceptualize and build impactful AI‑powered features and solutions.
• Construct and refine robust end‑to‑end ML pipelines, from efficient data ingestion to seamless model deployment in production environments ( MLOps Pipelines)
• Apply state‑of‑the‑art techniques, including transfer learning, reinforcement learning, and the fine‑tuning of pre‑trained models, with a strong focus on Large Language Models (LLMs) or Convolutional Neural Networks (CNNs).
• Deploy and serve models effectively using containerization (Docker), exposing them via performant APIs on leading cloud platforms.
• Proactively monitor and implement strategies for retraining production models to guarantee sustained performance, reliability, and stability over time.
• Continuously research and evaluate new AI trends and cutting‑edge technologies, actively identifying opportunities to integrate them into our product offerings.

Required Skill Set:

• Expert proficiency in Python, coupled with extensive experience using Pandas, NumPy, Scikit‑learn, and either TensorFlow or PyTorch.
• A solid understanding of core machine learning algorithms (supervised and unsupervised) and a deep comprehension of deep learning architectures including CNNs, RNNs, and especially Transformers.
• Proven hands‑on experience in fine‑tuning pre‑trained models, with particular emphasis on Large Language Models (LLMs) or NLP models
• A strong grasp of data preprocessing, feature engineering, and robust model evaluation/optimization techniques.
• Practical experience with model deployment using frameworks like Flask or FastAPI, combined with containerization via Docker.
• Demonstrated exposure to leading cloud platforms such as AWS (e.g., SageMaker, Lambda, S3) or GCP (e.g., Vertex AI, Cloud Run) for building and deploying scalable AI solutions.
• Knowledge of ETL pipelines, experience working with structured and unstructured data, and proficiency in basic SQL for data querying.
• Proven ability to thrive both independently and as an integral part of a collaborative team.

Preferred Qualifications:

• Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or related field.
• Prior experience in building AI systems in production environments.
• Publications, personal projects, or GitHub repos showcasing AI work are a plus.