Job Overview : Key Responsibilities :

- Design and Develop AI Solutions: Build advanced AI and NLP solutions focusing on large language models. Experiment with state-of-the-art Transformer architectures (e.g., BERT, GPT, LLaMA) to address complex language understanding and generation tasks.
- Advanced NLP Techniques: Implement and enhance NLP capabilities like text generation, summarization, and retrieval-augmented generation (RAG) to provide intelligent and contextually aware features in our solutions.
- Prompt Engineering & Fine-Tuning: Craft effective prompts and fine-tune LLMs to improve model performance for specific domains and use cases. Experiment with prompt strategies and training techniques to optimize generative models.
- Production Deployment & MLOps: Deploy and scale models in production environments, ensuring reliability and low-latency performance. Implement MLOps best practices (CI/CD pipelines, model monitoring, version control) to achieve robust, repeatable model deployments.
- Cloud AI Integration: Utilize AI/ML cloud services (AWS, GCP, Azure) for model training, deployment, and infrastructure management. Optimize cloud resources to handle large-scale training and inference efficiently.
- Model Optimization & Scaling: Continuously optimize model performance and implement scaling strategies to handle large datasets and high-volume usage.
- Cross-Functional Collaboration: Work closely with data scientists, software engineers, and product managers to integrate AI capabilities into products and solutions. Collaborate in cross-functional teams to gather requirements, brainstorm ideas, and ensure AI systems meet client needs and quality standards.
- Innovation and Research: Stay up-to-date with the latest AI research, papers,



and trends in the industry. Proactively experiment with current algorithms, models, and techniques to keep our solutions at the cutting edge.

Required Qualifications :

- Education & Experience: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience), plus 4+ years of hands-on experience in AI/ML engineering or a similar role.
- Deep Learning & LLM Expertise: Strong foundation in deep learning and NLP, with experience in transformer-based architectures and large language models (e.g., BERT, GPT series, LLaMA).
- Programming & Frameworks: Proficiency in Python programming and experience with major AI/ML frameworks and libraries - e.g., PyTorch, TensorFlow, and data libraries like NumPy, Pandas, scikit-learn. Familiarity with NLP/LLM tools such as Hugging Face Transformers, LangChain, and OpenAI APIs is highly desired.
- NLP & Generation: Proven experience developing NLP solutions, including working on text generation, summarization, conversational AI, or retrieval-augmented generation (RAG) systems.
- Model Tuning: Hands-on skills in prompt engineering and fine-tuning LLMs or other deep learning models to adapt them for specific tasks or domains. Experience with transfer learning and hyperparameter tuning for model optimization.
- Deployment & Cloud: Experience deploying machine learning models into production environments. Familiarity with deploying

Pay: ₹500,000.00 - ₹1,100,000.00 per year

Benefits :

- Provident Fund

Education :

- Bachelor's (required)

Experience :

- Python: 3 years (required)
- Data science: 4 years (required)

Location :

- Ahmedabad, Gujarat (preferred)

Work Location: Hybrid remote in Ahmedabad, Gujarat

📌 Senior Ai Engineer (Ahmedabad)
🏢 F(x) Data Labs
📍 Ahmedabad