Senior Software Engineer (Full Stack) (AI) (Onsite) (Hebbal)

Senior Software Engineer (Full Stack) (AI)

Role Overview

As a Senior Software Engineer (Full Stack) (AI), you will play a key role in designing, developing, and deploying generative AI, machine learning models, and AI systems. You will work closely with data scientists, software engineers, and business stakeholders to transform data-driven insights into real-world applications.

Responsibilities

• Design, develop, and optimize machine learning models for production environments.
• Build scalable AI systems, including data pipelines, model training, and deployment frameworks.
• Work with deep learning frameworks (TensorFlow, PyTorch) and traditional ML libraries (Scikit-learn, XGBoost).
• Collaborate with cross-functional teams to integrate AI solutions into existing products and services.
• Optimize models for performance, scalability, and efficiency in cloud or on-prem environments.
• Stay up to date with the latest advancements in AI/ML and apply best practices to ongoing projects.
• Conduct experiments, analyze performance, and iterate on models to enhance accuracy and efficiency.
• Mentor junior engineers and contribute to the AI/ML technical strategy.

Requirements

Education & Experience:

• Bachelors, Masters, or PhD in Computer Science, AI, Data Science, or a related field.
• 5+ years of strong experience with Java, Python, JavaScript, Typescript.
• Experience in AI/ML development, with a strong track record of building and deploying models.

Technical Skills:

• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, Airflow).
• Strong background in data preprocessing, feature engineering, and model optimization.
• Familiarity with deep learning architectures (CNNs, RNNs, Transformers) and NLP techniques.
• Experience with big data technologies (Spark, Hadoop) is a plus.
• Knowledge of DevOps, CI/CD for AI models, and containerization (Docker, Kubernetes) is a plus.

Soft Skills:

• Strong problem-solving and analytical skills.
• Ability to work in a fast-paced, collaborative environment.
• Excellent communication skills to convey complex AI concepts to stakeholders.