Accolite

AI Specialist

Posted On

Dec. 2, 2025

Location

Bengaluru, Karnataka

Experience Level

4 - 8 Years Exp.

Job Type

Full Time

Apply By

March 7, 2026

Job Description

Job Summary:

We are seeking a skilled AI Specialist to design, develop, and deploy AI-driven solutions across enterprise applications. The ideal candidate will have hands-on experience with machine learning, large language models (LLMs), data processing, and API-based integrations. This role involves building intelligent systems, optimizing AI pipelines, and collaborating with cross-functional teams to bring AI capabilities into production.

Key Responsibilities:

Develop, train, and deploy ML/AI models for prediction, classification, NLP, or automation tasks.

Build and integrate AI services and APIs into enterprise applications.

Work with LLMs, embeddings, vector search, and RAG pipelines (Retrieval-Augmented Generation).

Analyze datasets, perform feature engineering, and prepare data for model training.

Implement MLOps best practices for deployment, monitoring, and CI/CD automation.

Work with Python frameworks such as TensorFlow, PyTorch, Scikit-learn, FastAPI, Flask.

Integrate AI solutions with cloud platforms (AWS/Azure/GCP).

Collaborate with product, data engineering, and architecture teams on solution design.

Document models, pipelines, and technical workflows.

Ensure responsible AI usage, bias detection, and data governance compliance.

Required Qualifications:

Strong hands-on experience in Python for AI/ML model development.

Experience with Machine Learning, deep learning, or NLP techniques.

Experience implementing AI/LLM-based features (OpenAI, HuggingFace, Azure OpenAI, etc.).

Strong understanding of APIs, cloud platforms, and AI deployment workflows.

Experience working with vector databases (e.g., Pinecone, FAISS, Chroma) or RAG patterns.

Strong analytical, problem-solving, and communication skills.

Preferred Skills:

Experience with GenAI, agents, or automation frameworks.

Knowledge of Spark/Databricks for large-scale data processing.

Understanding of MLOps pipelines and observability.

Familiarity with Docker/Kubernetes.

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