Gen AI / ML Developer

At NestifyTech Solutions, looking a highly skilled and motivated Generative AI / Machine Learning Developer to design, develop, and deploy cutting-edge AI/ML solutions with a focus on generative models (e.g., LLMs, GANs, VAEs). The ideal candidate will have hands-on experience in developing machine learning pipelines, fine-tuning large models, and integrating AI capabilities into real-world applications.

Key Responsibilities

Develop and deploy generative AI models using technologies such as GPT, BERT, DALL·E, Stable Diffusion, or similar. Fine-tune and optimize large language models (LLMs) and other foundation models for specific business use cases. Build and maintain end-to-end ML pipelines including data ingestion, preprocessing, model training, evaluation, and deployment.

Collaborate with cross-functional teams including product managers, data engineers, and software developers to implement AI-driven features. Conduct research on the latest trends in generative AI and propose innovative solutions to real-world problems. Ensure the scalability, performance, and robustness of deployed AI/ML models.

Apply responsible AI principles including model interpretability, fairness, privacy, and security. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 3+ years of experience in ML/AI development; at least 1 year with generative AI. Proficiency in Python and ML libraries (TensorFlow, PyTorch, Hugging Face Transformers, etc.)

Experience working with LLMs (e.g., GPT, Claude, LLaMA, Mistral) or generative models (GANs, VAEs, Diffusion). Familiarity with MLOps tools (e.g., MLflow, Weights & Biases, Kubeflow). Experience with REST APIs, containerization (Docker), and cloud platforms (AWS, GCP, Azure).

Preferred Qualifications

Experience fine-tuning or training LLMs on proprietary data. Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate). Exposure to LangChain, LlamaIndex, or other LLM orchestration frameworks. Knowledge of prompt engineering and retrieval-augmented generation (RAG). Published research, open-source contributions, or patents in AI/ML.

Soft Skills: Strong problem-solving and analytical thinking. Effective communication and teamwork skills. Ability to work in a fast-paced, dynamic environment. Passion for innovation and continuous learning in AI/ML.