
AI/ML Engineer
6 days ago
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 (3–5 Years)
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.
- 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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