Ai / ml engineer

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

We are looking for an experienced AI / ML Engineer to join our team. The role involves developing, fine-tuning, and deploying advanced machine learning and deep learning models, including CNNs, RNNs, LLMs, and RAG pipelines , to power next-generation AI applications. This is a full-time on-site role for an AI / ML Engineer, located in Ahmedabad.

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 Py Torch, Tensor Flow, Scikit-learn, Pandas, Num Py.

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 / Fast API, 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.