Senior Engineer AIML - King of Prussia - Nexturn Inc

    Nexturn Inc
    Nexturn Inc King of Prussia

    1 week ago

    Description

    Job Description:
    Senior Engineer AI/ML (Databricks Certified)


    We are seeking a highly skilled AI Engineer with proven experience in developing, deploying, and optimizing AI models using the Databricks AI platform.

    The ideal candidate will have a strong background in machine learning, distributed data processing, and will be a champion of Databricks platform.

    Responsibilities

    Generative AI:
    Experience of LLM-based solutions (LlamaIndex, LangChain, RAG pipelines, or similar frameworks). Ability to integrate GenAI and Agentic AI into business workflows.
    Design and implement end-to-end Generative AI solutions on Databricks, leveraging Unity Catalog, MLflow, Delta Lake, and Vector Search
    Design, build, and deploy large-scale AI/ML models using the Databricks environment.
    Implement data validation, lineage, and monitoring using Delta Live Tables and Unity Catalog.
    Leverage Databricks' data engineering workflows for feature engineering, model training, and evaluation.
    Optimize training pipelines for efficiency, scalability, and accuracy.
    Integrate AI models into production systems using APIs and microservices.
    Build reusable ML pipelines using Databricks Repos, MLflow, and Feature Store.
    Implement robust testing, monitoring, and retraining protocols for deployed models.
    Ensure adherence to compliance, security, and performance standards.
    Stay updated on advancements in AI frameworks, distributed computing, and Databricks platform updates.

    Required Skills and Qualifications

    Bachelor's or Master's degree in Computer Science, Data Science, or related field.
    Cerified Databricks Certified Generative AI Engineer
    Proven experience developing AI solutions on Databricks.
    Strong knowledge of Python, PySpark, MLflow, Spark and Databricks Notebooks.
    Strong understanding and knowlege of Databricks platform features such as Unity Catalog, DLT, MosaicAI, Data Assets Bundles, etc.
    Experience with Transformer-based models, generative AI, and Databricks pipelines.
    Proficiency in integrating AI models with cloud-native architectures (AWS, Azure, or GCP).
    Solid understanding of MLOps practices, Data Assets bundles (CI/CD), and
    containerization (Docker, Kubernetes) on Databricks Platform.
    Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
    Strong problem-solving, analytical thinking, and communication skills.


    LEVEL OF EXPERTISE
    Databricks - 5 years (Must Have)
    Python - 8 years (Must Have)
    Generative AI - 8 years (Must Have)
    PySpark - 5 years (Must Have)
    Unity catalogue - 4 years (Nice to Have)
    ML flow - 4 years (Nice to Have)
    Delta Lake - 5 years (Nice to Have)
    Vector Search - 4 years (Nice to Have)
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