Machine Learning Engineer - Bengaluru / Bangalore - confidential

    confidential
    confidential Bengaluru / Bangalore

    4 days ago

    Full time
    Description
    • Define and implement model validation processes and business success criteria in data science terms .
    • Contribute to the architecture and data flow for machine learning models.
    • Rapidly develop and iterate minimum viable solutions (MVS) that address enterprise needs.
    • Conduct advanced data analysis and rigorous testing to enhance model accuracy and performance.
    • Work with Data Architects to leverage existing data models and create new ones as required.
    • Collaborate with product teams and business partners to industrialize machine learning models into Ericsson s enterprise solutions .
    • Build MLOps pipelines for continuous integration, continuous delivery, validation, and monitoring of AI/ML models.
    • Design and implement effective big data storage and retrieval strategies (indexing, partitioning, etc.).
    • Develop and maintain APIs for AI/ML models and optimize data pipelines.
    • Lead end-to-end ML projects from conception to deployment.
    • Stay updated on the latest ML advancements and apply best practices to enterprise AI solutions .

    Required Skills Experience

    • 4-6 years of hands-on experience in machine learning, AI, and data science .
    • Strong knowledge of ML frameworks (Keras, TensorFlow, Spark ML, etc.).
    • Proficiency in ML algorithms, deep learning, reinforcement learning (RL), and large language models (LLMs) .
    • Expertise in MLOps , including model lifecycle management and monitoring.
    • Experience with containerization orchestration (Docker, Kubernetes, Helm charts).
    • Hands-on expertise with workflow orchestration tools (Kubeflow, Airflow, Argo).
    • Strong programming skills in Python and experience with C++, Scala, Java, R .
    • Experience in API design development for AI/ML models .
    • Hands-on knowledge of Terraform for infrastructure automation.
    • Familiarity with AWS services (Data Lake, Athena, SageMaker, OpenSearch, DynamoDB, Redshift).
    • Strong understanding of self-hosted deployment of LLMs on AWS .
    • Experience in RASA, LangChain, LangGraph, LlamaIndex, Django, Open Policy Agent .
    • Working knowledge of vector databases, knowledge graphs, retrieval-augmented generation (RAG), agents, and agentic mesh architectures .
    • Expertise in monitoring tools like Datadog for K8S environments.
    • Ability to document, present , and communicate technical findings to business stakeholders .
    • Proven ability to contribute to ML forums, patents, and research publications .

    Educational Qualifications

    • B.Tech/B.E. in Computer Science , MCA, or a Master s in Mathematics/Statistics from a top-tier institute .

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