Software Engineer(AI/ML)

Redefine the future of customer experiences. One conversation at a time. At Nextiva, we’re reimagining how businesses connect, bringing together customer experience and team collaboration on a single, conversation centric platform. Powered by AI, driven by human innovation. Our culture is forward thinking, customer obsessed and built on the belief that meaningful connections drive better business outcomes. Whether it’s through our signature Amazing Service®, the technology we create, or the experiences we cultivate, connection is at the core of who we are. If you’re ready to collaborate with incredible people, make an impact, and help businesses everywhere deliver truly amazing experiences, this is where you belong. Location: This is an onsite role based at Nextiva’s Bengaluru office (Wilshire III by MFAR, 492, Hobli, RHB Colony, Mahadevapura, Bengaluru, Karnataka 560048). Working together onsite strengthens how we operate, enabling faster decisions, clearer communication, and stronger execution, so you can make a greater impact and move work forward with speed and clarity. In-Office Expectation: This role is expected to work onsite four days per week, with the potential to increase to five days per week, as required by the business. Specific scheduling and flexibility will be guided by your leader to support both team collaboration and individual productivity. We are seeking an experienced NLP and Generative AI Developer to design, develop, and deploy advanced AI models that solve complex business problems through natural language understanding and generation capabilities. The ideal candidate will implement cutting-edge GenAI solutions, optimize model performance, and collaborate with cross functional teams to align AI initiatives with business objectives. Key Responsibilities Model Development &

• Implementation
• Design and implement generative AI models using state-of-the-art techniques including GPT, VAE, GANs, and transformer architectures
• Develop and deploy NLP algorithms for text processing, semantic extraction, and language understanding systems
• Build and fine-tune large language models (LLMs) for specific use cases using transfer learning and domain adaptation techniques
• Implement prompt engineering strategies to optimize GenAI model performance and output quality Technical Execution
• Work with deep learning frameworks including TensorFlow, PyTorch, Keras, or scikit-learn to build scalable AI solutions
• Process and analyze large datasets using text representation techniques, word embeddings, and feature engineering
• Integrate NLP and GenAI components into existing systems and production pipelines with proper cloud or on-prem infrastructure
• Optimize existing models for improved performance, scalability, and efficiency through hyperparameter tuning and experimentation Research &
• Innovation
• Stay current with latest advancements in generative AI, machine learning, NLP techniques, and identify opportunities for integration
• Conduct research on emerging techniques such as RAG (Retrieval Augmented Generation) architecture, vector databases, and LangChain framework
• Evaluate model performance through rigorous testing frameworks and iterate to improve accuracy and reliability Required Qualifications Education &
• Experience
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
• Minimum 2-4 years of hands-on experience in NLP, machine learning, and generative AI development Technical Skills
• Strong proficiency in Python programming with experience in libraries like NumPy, SciPy, Pandas
• Deep understanding of NLP techniques including tokenization, named entity recognition, sentiment analysis, text classification, and sequence modeling
• Hands-on experience with LLMs such as OpenAI GPT, LLaMA, Claude, or similar models
• Expertise in deep learning architectures including LSTM, Transformers, attention mechanisms, and neural networks
• Experience with NLP libraries and frameworks such as Hugging Face, SpaCy, NLTK
• Knowledge of vector databases, embeddings, and semantic search technologies
• Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML models Soft Skills
• Strong problem-solving and analytical thinking abilities
• Excellent communication skills to convey complex technical concepts to diver