Ai/Ml Engineer

3 weeks ago

Industrial Area, India TecOrb Technologies - We Believe in Challenges Full time

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.

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