Data Science

Pineq Technology Labs; Chennai District, Bengaluru; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

Pineq Technology Labs is seeking an experienced Data Architect / Data Science professional to design scalable data architectures, develop AI/ML solutions, and build data pipelines for enterprise applications. The role involves working with large datasets, GenAI/LLMs, and cloud-based platforms.

The candidate should have 5+ years of experience, strong Python, SQL, data modeling, and ML frameworks (TensorFlow / PyTorch).

Qualifications

• Data Science & ML proficiency required.
• Strong Python implementation skills.
• Experience with AI/ML frameworks such as TensorFlow or PyTorch.
• Expertise in data architecture, data modeling and data pipelines.
• Proficient in SQL for data manipulation and querying.

Responsibilities

• Design scalable data architectures and integration solutions.
• Develop and deploy AI/ML models in production.
• Build data pipelines for training and production environments.
• Collaborate with cross-functional and business teams.
• Mentor team members and contribute to technical decisions.

Skills

Data Science & ML

Python

TensorFlow / PyTorch

Data Architecture & Modeling

SQL

Tools

Snowflake

AWS

Databricks

GenAI / LLM

MLOps / DevOps

Distributed Computing

Job description

Role: Data Architect / Data Science

Experience: 5+ Years
Location: PAN India
Education: 15 years of full-time education

Job Description

We are looking for an experienced Data Architect / Data Science professional to design scalable data architectures, develop AI/ML solutions, and build data pipelines for enterprise applications. The role involves working with large datasets, machine learning, GenAI/LLMs, and cloud-based data platforms.

Must Have

• Data Science & Machine Learning
• Python
• AI/ML frameworks TensorFlow / PyTorch
• Data Architecture, Data Modeling & Data Pipelines
• SQL

Good to Have

• Snowflake
• AWS
• Databricks
• GenAI / LLM
• MLOps / DevOps
• Distributed Computing

Responsibilities

• Design scalable data architectures and integration solutions.
• Develop and deploy AI/ML models in production.
• Build data pipelines for training and production environments.
• Work with cross-functional and business teams.
• Mentor team members and contribute to technical decisions.