AI Research Engineer

Epergne Solutions

Delhi

On-site

INR 4,000,000 - 7,000,000

Full time

2 days ago
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Job summary

Epergne Solutions in Bengaluru, India, seeks an experienced AI Research Engineer to design, develop, and deploy scalable ML systems focusing on LLMs, computer vision, and multimodal models.

You will build end-to-end pipelines, optimize costs, and ensure reliability in production. The role requires 7+ years of experience and strong Python/MLOps skills, with cross-functional collaboration.

Qualifications

  • 3–5+ years of experience in ML/AI engineering or software engineering.
  • Experience deploying production-grade ML applications.
  • Understanding of statistics, experimentation, and real-world performance analysis.

Responsibilities

  • Design and build AI features from data ingestion to real-time inference.
  • Create scalable, cost-efficient ML systems and services.
  • Develop training and inference pipelines for LLMs, CV, and multimodal models.
  • Create model evaluation frameworks, including offline and online experiments.
  • Collaborate with software, data, and product teams to deliver AI-powered features.
  • Deploy, monitor, and maintain ML models on containerised cloud infrastructure.
  • Investigate production incidents, improve reliability, and optimise performance.
  • Optimise training and inference costs via batching, quantisation, mixed precision, and GPU resource management.

Skills

Python
ML frameworks
End-to-end ML
MLOps tools
Docker
Kubernetes
GPU optimization
ONNX
RAG
Observability
Collaboration

Education

Bachelor/Master in CS/AI

Tools

MLflow
Weights&Biases
DVC
Airflow
Prefect
CI/CD

Job description

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.

Job Role: AI Research Engineer
Job Location: Bengaluru, India
Experience:- 7+ 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
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