Job Description

Job Title:

Associate ML Engineer (Experienced) - Python & LLMs

Location:

Valsad

Experience:

1-2 year

About the Role:

We are looking for an experienced and hands-on

Associate ML Engineer

with

1-2 years

of industry experience in

Python development

,

Machine Learning

, and

LLM-based solutions

. In this role, you will contribute to

designing, building, deploying, and optimizing AI/ML systems

--including generative AI applications, embeddings, vector search, and chatbot solutions. You will work across the full lifecycle of AI projects, from data processing to model deployment using

FastAPI

and database-backed systems.

Key Responsibilities

------------------------


Develop and maintain AI/ML models using Python, Scikit-Learn, PyTorch, or TensorFlow.
Build LLM-driven applications using GPT, BERT, or Transformer-based models.
Develop backend APIs (FastAPI) for deploying AI services.
Work with structured and unstructured data: cleaning, preprocessing, feature engineering, and evaluation.
Implement vector embeddings, similarity search, and LLM-based retrieval pipelines.
Optimize model performance and inference latency.
Integrate AI models with databases (MySQL, PostgreSQL, MongoDB, etc.).
Collaborate with product, backend, and mobile teams for end-to-end delivery.
Monitor, maintain, and retrain production ML models as needed.

Key Requirements:

Strong

Python programming skills

and clean coding practices.
Understanding of

Machine Learning and Deep Learning fundamentals

.
Familiarity with

LLMs (GPT, BERT, Transformers)

and modern ML frameworks.
Experience with

FastAPI

and database integration (e.g., MySQL).
Ability to work with datasets: preprocessing, analysis, and model evaluation.
Good debugging, problem-solving, and analytical skills.
Passion for

generative AI, chatbots, and applied AI solutions

.

Preferred Skills:

Understanding of

prompt engineering, embeddings, or LLM fine-tuning

.
Experience with cloud AI platforms (Azure AI, AWS Bedrock, OpenAI API, Hugging Face).
Understanding of model deployment, CI/CD, and containerization (Docker).
Basic understanding of data pipelines, ETL workflows, or MLOps practices.
Knowledge of

data visualisation, model deployment, and production AI systems

.

Education:

B.Tech / B.E / M.Tech / MCA in

Computer Science, AI, Data Science, or related fields

.

Why Join Us:

Work on

cutting-edge generative AI and LLM projects

.
Build

end-to-end AI solutions

with Python, FastAPI, and databases.
Fast-growing, innovation-driven, and collaborative environment.
Exposure to production-grade deployments and modern AI architecture.