Veeda CR
AI Developer
Skills
1 month ago
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Important information
Contract type:
Permanent
Salary:
₹350,000 – ₹500,000 / year
Location:
Ahmedabad, Gujarat, India
Work mode:
Onsite
Published on:
8 September 2026
What they need
Role & responsibilities
Work on the design, development, and deployment of Generative AI models.
Implement AI/ML models for text, image, and data generation tasks
Fine-tune pre-trained models (e.g., GPT, Claude, LLaMA, Stable Diffusion, etc.) for business-specific needs.
Integrate Generative AI solutions into web and enterprise applications.
Collaborate with cross-functional teams to gather requirements and deliver AI-powered solutions.
Conduct testing, optimization, and performance tuning of AI models.
Document processes, workflows, and maintain project deliverables.
Preferred candidate profile
Required Skills & Tools:
Programming Languages: Python (mandatory), basic knowledge of JavaScript/PHP (plus).
Generative AI Frameworks: Hugging Face, LangChain, RAG (Retrieval Augmented Generation).
ML/DL Libraries: TensorFlow, PyTorch, Keras.
Generative Models: GPT, LLaMA, Stable Diffusion, DALL•E, MidJourney (experience in at least one).
Cloud Platforms: Azure AI, Google Cloud Vertex AI, AWS Bedrock/OpenAI APIs.
Databases: MySQL/PostgreSQL, Vector DBs (Pinecone, FAISS, Weaviate).
Version Control: Git/GitHub.
MLOps Tools (Good to have): MLflow, Docker, Kubernetes.
Soft Skills:
Strong problem-solving ability and logical thinking.
Good communication and documentation skills.
Ability to work independently and in a team environment.
Eagerness to learn and adapt to new AI trends.
Nice-to-Have:
Experience with REST APIs and microservices.
Exposure to prompt engineering and AI ethics/compliance.
Tools & Technologies Candidate Should Know (for Generative AI Project Development)
Programming: Python (must), optionally JavaScript/PHP for integration.
Generative AI Libraries: Hugging Face, LangChain, OpenAI API, LLaMA models.
ML Frameworks: TensorFlow, PyTorch.
Databases: SQL + Vector DB (Pinecone, FAISS).
Cloud AI Services: Google Vertex AI, Azure AI, AWS Bedrock.
MLOps Tools: MLflow, Docker, GitHub Actions.
Integration Tools: REST APIs, FastAPI/Flask, Laravel backend for enterprise integration.
Visualization: Power BI / Streamlit / Dash (optional for dashboards).
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