AI/ML Engineer

Job Description

AI/ML Engineer (Mtech or PhD) ? LLMs, RAG, Reinforcement Learning Position: AI/ML Engineer (Mid-Level) Experience: Does not required Location: Noida, UP Employment Type: Full-time Studies : Mtech or PhD About the Role We are building enterprise-grade AI/ML solutions including SLMs, LLMs, RAG- based knowledge systems, reinforcement learning, and agentic AI, As a Mid-level AI/ML Engineer, you will design, train, and deploy machine learning models, collaborate with our product and engineering teams, and ensure scalable integration of AI models into real-world applications. This role is ideal for someone with a strong hands-on background in NLP, deep learning, and reinforcement learning, who is eager to grow by working on cutting-edge AI projects at scale. Key Responsibilities ? Design, train, and fine-tune ML/DL models (with focus on transformers, SLMs, LLMs, and recommender systems). ? Implement RAG pipelines using vector databases (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) for optimizing 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, AWS/GCP/Azure ML services. ? Monitor and optimize model performance (latency, accuracy, hallucination rates). ? Use MLflow / 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 in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow). ? Solid understanding of NLP and LLM architectures (Transformers, BERT, GPT, LLaMA, Mistral). ? Practical experience with vector databases (Pinecone, or FAISS or PgVector). ? Basic Knowledge with MLOps tools ? Docker, Kubernetes, MLflow, CI/CD. ? Basic Knowledge of cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure ML). ? Good grasp of linear algebra, probability, statistics, optimization. ? Strong debugging, problem-solving, and analytical skills. ? Familiarity with Agile methodologies (Scrum, Jira, Git). Nice-to-Have Skills ? Experience with RLHF pipelines. ? Open-source contributions in AI/ML. Soft Skills ? Strong communication ? able to explain AI concepts to technical & non-technical stakeholders. ? Collaborative ? works well with product, design, and engineering teams. ? Growth mindset ? eager to learn new AI techniques and experiment. ? Accountability ? able to deliver end-to-end model pipelines with minimal supervision. ? Can works in a team. What We Offer ? Work on cutting-edge AI projects with real-world enterprise impact. ? Exposure to LLMs, reinforcement learning, and agentic AI. ? Collaborative Startup & Service culture with room for fast growth. ? Competitive compensation + performance-based incentives.