AI Development Engineer

Company Description

ReLU Technologies engineers the future of intelligent systems by pioneering advanced AI applications, frameworks, and intelligent software platforms. We specialize in high-performance AI models, real-time decision engines, and adaptive automation frameworks built on a robust embedded software foundation. Our solutions deliver deterministic performance and mission-critical reliability across cloud, edge, and device ecosystemsempowering organizations to deploy scalable, efficient, and resilient AI-driven systems powered by deep engineering expertise

Job Title: AI Development Engineer

Location: Onsite Bangalore

Experience: 36 years (flexible based on skill depth)

Employment Type: Full-time

Role Description

We are looking for an AI Development Engineer who will design, develop, train, tune, deploy, and maintain AI/ML models across the full lifecyclefrom data preparation to production-grade inference pipelines. The role requires hands-on expertise in modern AI frameworks, scalable pipelines, and real-world deployment environments.

Key Responsibilities

Model Development & Training

• Design, train, fine-tune, and evaluate machine learning and deep learning models
• Perform hyperparameter tuning, model optimization, and performance benchmarking
• Work with supervised, unsupervised, and reinforcement learning approaches as required
• Optimize models for accuracy, latency, memory, and power consumption

Data Preparation & Feature Engineering

• Collect, clean, preprocess, and validate structured and unstructured datasets
• Perform feature engineering, data augmentation, and dataset versioning
• Ensure data quality, consistency, and bias monitoring

Inference & Deployment

• Develop efficient inference pipelines for batch, real-time, and streaming use cases
• Deploy models to cloud, on-prem, and edge environments
• Optimize models using techniques such as quantization, pruning, and distillation
• Integrate AI models with applications via APIs and microservices

AI Pipelines & MLOps

• Build end-to-end AI/ML pipelines (training validation deployment monitoring)
• Implement CI/CD pipelines for AI workflows
• Monitor model drift, performance degradation, and retraining triggers
• Manage experiment tracking, model versioning, and reproducibility

Frameworks & Tools

• Work extensively with AI frameworks and libraries such as:
• TensorFlow / PyTorch / JAX
• Hugging Face, ONNX, OpenVINO, TensorRT (as applicable)
• Use data and pipeline tools like Airflow, MLflow, Kubeflow, or equivalent
• Collaborate closely with product, platform, and infrastructure teams

Required Skills & Qualifications

• Strong proficiency in Python (mandatory); experience with C++ is a plus
• Solid understanding of machine learning, deep learning, and statistical modeling
• Hands-on experience with at least one major AI framework (PyTorch or TensorFlow preferred)
• Experience building and deploying AI models into production environments
• Familiarity with REST APIs, containers (Docker), and orchestration (Kubernetes)
• Understanding of cloud platforms (AWS / Azure / GCP) or on-prem deployments
• Strong problem-solving and debugging skills

Preferred Qualifications

• Experience with edge AI or resource-constrained deployments
• Knowledge of distributed training and large-scale model optimization
• Exposure to NLP, computer vision, or multimodal AI systems
• Familiarity with data security, privacy, and responsible AI practices