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    Job · 20656989

    INDORE · FULLTIME

    AI Research Engineer

    Epergne Solutions

    Epergne Solutions

    Indore · onsite · Posted 11d ago

    Sourced fromFoundit
    Not disclosed3–5 yrsfulltimeIndore

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    Section · 01

    About this role

    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:-
    • Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
    • 35+ 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

    Sourced from foundit

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    Section · 02

    Skills

    GPU optimisationPrometheusGrafanaDockerKubernetesmixed precision techniquesRetrieval Augmented Generationmlflowapache airflowvector databasesTensorRTOnnxMLOps toolsOpenTelemetryDVCllm fine-tuningMonitoring ToolsPytorchTensorflowPrefectBatchingWeights BiasesPython

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