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AI Research Engineer

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Onsite

AI Research Engineer

Epergne Solutions

AI Research Engineer

Skills

DockerPythonPyTorchTensorFlowGrafanaMachine LearningAIPrometheusKubernetesApache Airflow

2 months ago

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Important information


Contract type:

Permanent

Location:

Delhi, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


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

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