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Epergne Solutions · Bengaluru, Karnataka, India

AI Research Engineer

full timePosted Aug 13
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Stack mentioned

llmpythonpytorchtensorflowmlopsmlflowapache-airflowprefectdockerkubernetesci/cdonnxragobservabilityprometheusgrafanaopentelemetrystatisticsmachine-learningcomputer-vision

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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