Software Engineer - AI Software & Platform

United States Digital Space LLC; Karnataka; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

United States Digital Space LLC is seeking a Machine Learning Engineer to design, develop, and optimize advanced ML models for NLP and machine perception. You will work with transformer-based architectures and CNNs, building scalable pipelines and production-ready solutions in collaboration with product, research, and engineering teams.

Responsibilities include implementing models with TensorFlow/PyTorch/JAX, training and evaluating performance, and improving data processing workflows.

Qualifications

• Bachelor's degree with 5+ years of relevant industry experience, or Master's degree with 3+ years of relevant industry experience, or PhD with 0+ years of relevant industry experience.
• Strong experience developing and deploying deep learning models using modern machine learning frameworks (e.g., TensorFlow, PyTorch, JAX, or similar).
• Hands-on experience with neural network architectures, including transformer-based models and convolutional neural networks.
• Experience with machine learning model training, evaluation, optimisation, and production deployment.
• Proficiency in Python and software development best practices.
• Experience working with data preprocessing, feature engineering, and model performance evaluation.

Responsibilities

• Design, develop, and optimize deep learning models for NLP and/or machine perception applications.
• Partner with cross-functional teams to build scalable machine learning solutions and data pipelines.
• Develop new models or enhance existing architectures to improve accuracy, efficiency, and reliability.
• Implement and fine-tune models using industry-standard machine learning frameworks.
• Monitor, evaluate, and optimise model performance for production deployment.
• Improve data quality, automate training workflows, and develop reusable, scalable code.
• Collaborate with engineering teams to integrate and deploy machine learning models across platforms.

Skills

Python

TensorFlow

PyTorch

JAX

NLP

Transformer models

CNNs

Data pipelines

MLOps

Data preprocessing

Education

Bachelor's degree

Master's degree

PhD

Tools

Keras

MLflow

Docker

Git

Job description

Meet the Team

Join a team focused on advancing the next generation of AI and machine learning technologies. We design, develop, and optimise state-of-the-art deep learning models for natural language processing (NLP) and machine perception applications. Working closely with product, research, and engineering teams, you'll help bring innovative AI solutions from concept to production, enabling scalable, efficient, and reliable intelligent systems that power real-world applications.

Your Impact

As a Machine Learning Engineer, you will design, develop, and optimise advanced machine learning algorithms and neural network architectures for NLP and/or machine perception tasks. You will leverage modern deep learning techniques including transformer-based architectures, convolutional neural networks (CNNs), knowledge distillation, student‑teacher models, generative adversarial networks (GANs), and optimisation strategies to improve model accuracy, efficiency, scalability, and production readiness.

In this role, you will:

• Design, develop, and optimize deep learning models for NLP and/or machine perception applications.
• Partner with cross‑functional teams to build scalable machine learning solutions and data pipelines.
• Develop new models or enhance existing architectures to improve accuracy, efficiency, and reliability.
• Implement and fine‑tune models using industry‑standard machine learning frameworks.
• Monitor, evaluate, and optimise model performance for production deployment.
• Improve data quality, automate training workflows, and develop reusable, scalable code.
• Collaborate with engineering teams to integrate and deploy machine learning models across platforms.

Minimum Qualifications

• Bachelor's degree with 5+ years of relevant industry experience, or Master's degree with 3+ years of relevant industry experience, or PhD with 0+ years of relevant industry experience.
• Strong experience developing and deploying deep learning models using modern machine learning frameworks (e.g., TensorFlow, PyTorch, JAX, or similar).
• Hands‑on experience with neural network architectures, including transformer‑based models and convolutional neural networks.
• Experience with machine learning model training, evaluation, optimisation, and production deployment.
• Proficiency in Python and software development best practices.
• Experience working with data preprocessing, feature engineering, and model performance evaluation.

Preferred Qualifications

• Experience working with Large Language Models (LLMs), Generative AI, multimodal AI, or foundation models.
• Experience optimising models for inference efficiency, scalability, latency, and resource utilisation.
• Knowledge of distributed model training, model compression, quantisation, or edge AI deployment.
• Experience building production‑scale machine learning pipelines and MLOps workflows.