Sr Software Research Engineer_Banglore / Chennai

Tata Consultancy Services; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading IT services company in Bengaluru is seeking a Sr Software Research Engineer with 5 to 10 years of experience. The ideal candidate will have proficiency in deep learning frameworks and Python, along with a strong understanding of NLP and reinforcement learning. This full-time position focuses on building neural networks and contributing to AI research. Join a dynamic team to innovate in the IT sector.

Qualifications

• 5 to 10 years of experience in software engineering, preferably in AI/ML.
• Understanding of GPU/TPU computation in deep learning.
• Ability to read and implement findings from scientific papers.

Responsibilities

• Build and train deep neural networks for various NLP tasks.
• Contribute to AI research through publications or projects.
• Set up and manage applications on low-code/no-code platforms.

Skills

Deep learning frameworks (TensorFlow, PyTorch)

Natural Language Processing (NLP)

Python

Reinforcement learning

Agent-based modelling

Education

Bachelor's or Master's in Computer Science, Data Science, or AI

Tools

Langflow

Job description

Sr Software Research Engineer (Bangalore / Chennai)

Role: Sr Software Research Engineer

Experience: 5 to 10 years

Location: Bangalore / Chennai

Contact: [e-mail]

Deep Learning and NLP Skills

• Proficiency in building and training deep neural networks using frameworks like TensorFlow, PyTorch, etc.
• Understanding of transformer architectures like BERT, GPT, T5, etc.
• Knowledge of sequence‑to‑sequence models, attention mechanisms, and embeddings.
• Experience with NLP tasks such as tokenization, named entity recognition, and sentiment analysis.
• Strong understanding of the fundamentals of reinforcement learning, including concepts like Markov Decision Processes, Q‑learning, and policy gradients.
• Experience with modern RL libraries like OpenAI Gym, Ray's RLlib, or Stable Baselines.
• Practical knowledge of reinforcement learning in non‑stationary environments and using human feedback as rewards.
• Familiarity with techniques like gradient clipping, learning rate schedules, regularization, and dropout.
• Understanding of distributed training and optimization techniques to handle large datasets and models.

Computational Skills

• Proficiency in Python and other programming languages common in the AI/ML domain.
• Knowledge of GPU and TPU computation, especially in the context of deep learning.

Research Acumen

• Ability to read, understand, and implement findings from scientific papers, especially those related to LLMs and their optimizations.
• Contributions to the AI research community through publications, conferences, or open‑source projects can be an advantage.

Deep Understanding of LLMs

• Familiarity with the nuances of large language models, their strengths, and potential pitfalls.
• Awareness of typical business use cases for LLMs, from customer support automation to content generation.

Low‑code/No‑code Platform Expertise

• Proficiency in using and configuring platforms like Langflow.
• Experience in setting up, deploying, and managing applications on such platforms.

Agent‑based Modelling Skills

• Strong understanding of defining, designing, and implementing agents, their behaviours, and interactions.
• Ability to set up policies, constraints, and orchestrate chains of agents to fulfil specific business processes or workflows.

Educational Background

• A Bachelor's or Masters (preferably) in Computer Science, Data Science, Artificial Intelligence, or related fields.

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Information Technology

Industries: IT Services and IT Consulting and IT System Testing and Evaluation