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Skills Required

ai ml technology software development collaboration tuning learning power design data preprocessing engineering vision retrieval model scalability efficiency research pytorch tensorflow flask fastapi docker aws gcp communication teamwork mlflow spark reinforcement

Work Mode

On-site

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


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.
  • 5–6 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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