AI Research Engineer

Epergne Solutions; Chennai District; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

Epergne Solutions is seeking an AI Research Engineer to design, develop, and deploy scalable machine learning systems. You will focus on building LLM, computer vision, and multimodal pipelines, deploying models into production, and improving reliability, performance, and cost efficiency.

You will design end-to-end ML pipelines, collaborate with cross-functional teams, and work with containerised and cloud-based infrastructure to deliver AI-powered features.

Qualifications

• Strong programming in Python and ML frameworks (PyTorch, TensorFlow).
• Experience building end-to-end ML pipelines from data prep to deployment and monitoring.
• Familiarity with MLOps tools like MLflow, Weights & Biases, DVC, Airflow or Prefect.
• Experience with Docker, Kubernetes, containerised deployments, and CI/CD practices.
• Knowledge of GPU optimisation, ONNX, TensorRT, batching, and mixed precision techniques.

Responsibilities

• Design and develop AI features from data ingestion through real-time model inference.
• Build scalable, cost-efficient, and observable ML systems and services.
• Develop training and inference pipelines for LLM, computer vision, and multimodal models.
• Create model evaluation frameworks, including offline evaluation, online experiments, and user feedback integration.
• Collaborate with software engineering, data, and product teams to deliver AI-powered features.
• Deploy, monitor, and maintain ML models using containerised and cloud-based infrastructure.
• Investigate production incidents, improve system reliability, and optimise performance.
• Optimise training and inference costs through batching, quantisation, mixed precision, and GPU resource management.

Skills

Python

ML Frameworks

End-to-End ML

MLOps

Docker/Kubernetes

GPU/Quantisation

RAG/LLM Tuning

Observability

Problem Solving

Communication

Education

Bachelor's or Master's in CS/AI

Tools

MLflow

Weights & Biases

DVC

Airflow

CI/CD

Job description

Job Description:

Job Role:

AI Research Engineer

Job Location:

Bengaluru, India

Experience:

3-5+ Years

Role Summary:

We are seeking an AI Research Engineer to design, develop, and deploy scalable machine learning systems and AI-powered features. The role focuses on building LLM, computer vision, and multimodal machine learning pipelines, deploying models into production, and improving system reliability, performance, and cost efficiency.

Key Responsibilities:

• Design and develop AI features from data ingestion through real-time model inference.
• Build scalable, cost-efficient, and observable machine learning systems and services.
• Develop training and inference pipelines for LLM, computer vision, and multimodal AI models.
• Create model evaluation frameworks, including offline evaluation, online experiments, and user feedback integration.
• Collaborate with software engineering, data, and product teams to deliver AI-powered features.
• Deploy, monitor, and maintain machine learning models using containerised and cloud-based infrastructure.
• Investigate production incidents, improve system reliability, and optimise operational performance.
• Optimise training and inference costs through batching, quantisation, mixed precision, and GPU resource management.

Required Skills:

• Strong proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.
• Experience building end-to-end machine learning pipelines, including data preparation, training, evaluation, deployment, and monitoring.
• Knowledge of MLOps tools such as MLflow, Weights & Biases, DVC, Airflow, or Prefect.
• Experience with Docker, Kubernetes, containerised deployments, and CI/CD practices.
• Understanding of GPU optimisation, ONNX, TensorRT, batching, and mixed precision techniques.
• Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM fine-tuning approaches.
• Knowledge of observability and monitoring tools such as Prometheus, Grafana, or OpenTelemetry.
• Strong analytical, problem-solving, and collaboration skills.

Qualifications & Experience:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 3–5+ years of experience in applied machine learning, AI engineering, or software engineering.
• Experience developing and deploying production-grade machine learning applications.
• Understanding of statistics, experimentation, model evaluation, and real-world performance analysis.

Preferred Attributes:

• Hands-on experience with LLMs, computer vision, or multimodal AI systems.
• Ability to balance research innovation with production engineering requirements.
• Strong ownership mindset and experience working in cross-functional teams.
• Excellent communication and technical documentation skills