AI/ML Engineer

We are seeking a highly skilled and motivated AI/ML Engineer with a strong software development background and hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern ML pipelines. You will play a key role in designing, developing, and deploying AI-driven solutions that push the boundaries of what's possible in real-world applications. Key Responsibilities: • Design, develop, and deploy AI/ML solutions, focusing on LLMs and generative models for NLP and multimodal tasks. • Implement Retrieval-Augmented Generation (RAG) systems by integrating vector databases, embedding models, and scalable retrieval pipelines. • Fine-tune and optimize foundation models (e.g., GPT, LLaMA, Mistral, Claude) for custom enterprise use cases. • Build end-to-end ML pipelines including data preprocessing, model training, evaluation, and deployment using tools like MLflow, Airflow, or Kubeflow. • Collaborate with cross-functional teams including product managers, data scientists, and backend engineers to integrate AI models into production systems. • Monitor, test, and continuously improve deployed AI models for performance, accuracy, fairness, and interpretability. • Stay current with the latest research and advancements in AI/ML, Generative AI, and open-source LLMs. Required Qualifications: • Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field. • 3+ years of software development experience in Python, Java, or other major languages, with strong understanding of system design and APIs. • Proven experience in developing and deploying ML/AI solutions, particularly in the domain of Generative AI, LLMs, Transformers, and RAG systems. • Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, etc. • Strong understanding of vector search technologies (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embeddings. • Familiarity with cloud platforms (AWS, Azure, GCP) and containerized environments (Docker, Kubernetes). Nice to Have: • Experience with multi-modal models (e.g., text-to-image, audio-to-text). • Understanding of MLOps best practices, CI/CD for ML systems. • Exposure to privacy, safety, bias mitigation, and ethical AI concerns. • Contributions to open-source AI/ML projects or published research. Soft Skills: • Strong analytical and problem-solving skills. • Ability to communicate complex technical concepts to non-technical stakeholders. • Collaborative mindset and eagerness to learn and share knowledge. What We Offer: • Opportunity to work on cutting-edge AI/ML projects in a high-impact environment. • Access to state-of-the-art tools and infrastructure. • Competitive compensation and benefits. • A collaborative and inclusive culture focused on innovation.