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Job Type

Full Time

Job Description

Company Description

Zaptech Solutions is a fast-growing technology solutions provider delivering innovative products and services in AI, ML, cloud, and software development. We pride ourselves on creating intelligent, scalable solutions that make real-world impact. Our team thrives on innovation, collaboration, and continuous learning.


Role Description

AI/ML Engineer (3–5 Years)


Key Responsibilities

  • Design, develop, and deploy end-to-end ML/AI models.
  • Work with large datasets: data cleaning, preprocessing, feature engineering, and EDA.
  • Develop and optimize

    deep learning models (CNNs, RNNs, Transformers)

    for computer vision, NLP, and sequential data.
  • Fine-tune and optimize

    large language models (LLMs)

    for domain-specific use cases.
  • Build and implement

    RAG (Retrieval-Augmented Generation)

    pipelines with vector databases.
  • Ensure model performance, scalability, and efficiency in real-time production environments.
  • Collaborate with cross-functional teams (data engineers, developers, product managers).
  • Stay updated on the latest research and trends in AI/ML and apply them to projects.


Required Skills & Qualifications

  • Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or related field.
  • 3–5 years of proven experience in AI/ML engineering.
  • Proficiency in

    Python

    with libraries/frameworks such as PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy.
  • Strong understanding of

    ML concepts, deep learning (CNN, RNN, Transformers), NLP, and computer vision

    .
  • Hands-on experience in

    LLM fine-tuning and prompt engineering

    .
  • Familiarity with

    vector databases

    (Pinecone, FAISS, Weaviate, Milvus) for RAG-based solutions.
  • Experience deploying ML models using Flask/FastAPI, Docker, and cloud platforms (AWS/GCP/Azure).
  • Strong analytical and problem-solving skills.
  • Good communication and teamwork skills.


Nice-to-Have

  • Knowledge of

    MLOps tools

    (MLflow, Kubeflow, Airflow).
  • Experience with big data frameworks (Spark, Hadoop).
  • Familiarity with

    generative AI architectures

    and reinforcement learning.


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