AI/ML Engineer

As an AI/ML Engineer at our company, you will be responsible for designing, training, and deploying machine learning models. Your role will involve collaborating with product and engineering teams to ensure scalable integration of AI models into real-world applications. This position is ideal for individuals with a strong background in NLP, deep learning, and reinforcement learning, who are eager to work on cutting-edge AI projects at scale. **Key Responsibilities:** - Design, train, and fine-tune ML/DL models with a focus on transformers, SLMs, LLMs, and recommender systems. - Implement RAG pipelines using vector databases such as Pinecone, Weaviate, FAISS, and frameworks like LangChain or LlamaIndex. - Contribute to LLM fine-tuning using LoRA, QLoRA, and PEFT techniques. - Work on reinforcement learning (RL/RLHF) to optimize LLM responses. - Build data preprocessing pipelines for structured and unstructured datasets. - Collaborate with backend engineers to expose models as APIs using FastAPI/Flask. - Ensure scalable deployment using Docker, Kubernetes, and AWS/GCP/Azure ML services. - Monitor and optimize model performance in terms of latency, accuracy, and hallucination rates. - Utilize MLflow and Weights & Biases for experiment tracking and versioning. - Stay updated with the latest research papers and open-source tools in AI/ML. - Contribute to code reviews, technical documentation, and best practices. **Required Skills & Qualifications:** - Strong proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow). - Solid understanding of NLP and LLM architectures including Transformers, BERT, GPT, LLaMA, and Mistral. - Practical experience with vector databases such as Pinecone, FAISS, or PgVector. - Basic knowledge of MLOps tools like Docker, Kubernetes, MLflow, and CI/CD. - Familiarity with cloud platforms such as AWS Sagemaker, GCP Vertex AI, or Azure ML. - Good grasp of linear algebra, probability, statistics, and optimization. - Strong debugging, problem-solving, and analytical skills. - Familiarity with Agile methodologies like Scrum, Jira, and Git. **Nice-to-Have Skills:** - Experience with RLHF pipelines. - Open-source contributions in AI/ML. **Soft Skills:** - Strong communication skills to explain AI concepts to technical and non-technical stakeholders. - Collaborative nature to work effectively with product, design, and engineering teams. - Growth mindset with a willingness to learn new AI techniques and experiment. - Accountability to deliver end-to-end model pipelines with minimal supervision. - Ability to work effectively in a team environment. Join us to work on cutting-edge AI projects with real-world enterprise impact, exposure to LLMs, reinforcement learning, and agentic AI, a collaborative startup culture with rapid growth opportunities, and competitive compensation with performance-based incentives.,