Deepmindz Innovations is hiring an experienced AI Engineer to join its team in Noida. This opportunity is designed for professionals with strong hands-on experience in Artificial Intelligence, Machine Learning, Generative AI, LLMs, NLP, LangChain and RAG. Candidates who can join immediately or within 15 days are preferred.
📌 Job Details
📍 Company: Deepmindz Innovations
💼 Role: AI Engineer
📍 Location: Noida
🧑💻 Experience: 4–5 Years
⏳ Joining: Immediate Joiner / Up to 15 Days
🛠️ Primary Skills: Python, AI/ML, Generative AI, LLMs, NLP, LangChain, RAG, OpenAI APIs
🤖 Additional Skills: TensorFlow/PyTorch, Deep Learning, Model Deployment, MLOps
📩 Application: dharya.aggarwal@deepmindz.co
🏢 About Deepmindz Innovations
Deepmindz Innovations is hiring for an AI-focused engineering position that combines traditional machine learning with the rapidly growing areas of Generative AI and Large Language Models. The technology stack mentioned in the hiring requirement covers the complete AI lifecycle—from developing ML and deep learning models to building LLM-powered applications, implementing RAG pipelines and deploying models into production environments.
For an experienced AI Engineer, this makes the position particularly relevant because it requires knowledge across both AI development and production implementation, rather than focusing only on model experimentation.
⭐ Why This Role Is Good for Experienced Professionals?
🔹 Generative AI: Work with modern LLM-based application architectures and AI solutions.
🔹 RAG: Develop systems that combine retrieval mechanisms with language models to improve contextual responses.
🔹 LLM APIs: Build practical applications using models through APIs such as OpenAI.
🔹 AI Engineering: Combine Python, ML, NLP and deep learning into production-oriented solutions.
🔹 Deployment & MLOps: Understand how AI models move from development environments into reliable production systems.
🔹 Career Growth: The combination of traditional ML and GenAI skills can be useful for professionals targeting AI Engineer, GenAI Engineer or ML Engineer positions.
🎯 Skills Required for AI Engineer
Candidates should prepare for a combination of programming, machine learning and Generative AI capabilities:
🐍 Python: Strong programming, data handling, API integration and application development skills.
🧠 Machine Learning: Understanding of supervised and unsupervised learning, feature engineering, model evaluation and optimization.
🔥 Deep Learning: Practical knowledge of neural networks and frameworks such as TensorFlow or PyTorch.
💬 NLP: Understanding of text processing, embeddings, tokenization and language-model concepts.
🤖 Generative AI & LLMs: Knowledge of prompting, model APIs, embeddings, context handling and LLM application design.
🔗 LangChain: Ability to work with chains, retrievers, tools and LLM-based workflows.
📚 RAG: Understanding of document ingestion, chunking, embeddings, vector search and retrieval pipelines.
🚀 Model Deployment: Experience deploying AI/ML models through APIs or production services.
⚙️ MLOps: Familiarity with model lifecycle management, monitoring, versioning and deployment practices.
📝 Expected Interview Rounds
The exact interview process for Deepmindz Innovations is not specified in the provided hiring post, so candidates should not assume a fixed number of rounds. Based on the responsibilities and technical stack, preparation should cover a likely combination of:
🔹 Technical Screening: Questions around Python, ML fundamentals, NLP and AI concepts.
🔹 GenAI/LLM Technical Round: Deep discussion around LLMs, prompt engineering, RAG, LangChain, embeddings and OpenAI APIs.
🔹 Project/Practical Discussion: Candidates may be asked to explain previous AI projects, architecture decisions, challenges and measurable outcomes.
🔹 Deployment/MLOps Discussion: Questions may focus on deploying models, APIs, scalability, monitoring and production reliability.
🔹 Managerial/HR Round: Discussion around experience, availability, compensation, role expectations and joining timeline.
💰 Salary Range
The salary range is not disclosed in the provided job posting. Candidates should confirm the compensation structure directly with the recruiter during the hiring process. For a 4–5 year AI Engineer role with substantial GenAI, LLM, RAG and MLOps requirements, candidates should evaluate the complete package based on their hands-on expertise, production experience and current market value rather than focusing only on the designation.
📚 Preparation Tips
🎯 Build one complete RAG project: Be ready to explain document loading, chunking, embeddings, vector databases, retrieval and response generation.
🤖 Revise LLM architecture: Understand tokens, context windows, embeddings, temperature, hallucinations and model limitations.
🔗 Practice LangChain: Know how retrievers, chains, prompts, tools and agents work together.
💻 Strengthen Python: Revise OOP, APIs, error handling, asynchronous programming and commonly used AI libraries.
🧠 Revise ML/DL fundamentals: Prepare model selection, overfitting, regularization, evaluation metrics and neural-network concepts.
🚀 Prepare deployment examples: Be able to explain how you deployed an AI/ML solution, including API design, containers, cloud infrastructure or monitoring where applicable.
⚙️ Understand MLOps: Revise CI/CD for ML, model versioning, experiment tracking, monitoring and retraining workflows.
💬 Know OpenAI API integration: Be prepared to explain API calls, prompt construction, structured outputs, error handling and cost/performance considerations.
📄 Resume Tips for This AI Engineer Role
Your resume should immediately demonstrate hands-on GenAI and production experience. Put Python, Generative AI, LLMs, RAG, Lang Chain, NLP, OpenAI APIs and MLOps prominently in the technical skills section if you genuinely possess them.
Instead of writing “worked on AI project,” mention the exact solution and your contribution—for example, “Developed a RAG-based knowledge assistant using Python, embeddings and LLM APIs.” Add measurable results such as response-time improvements, accuracy improvements, reduced manual effort or application scale whenever possible.
Also highlight deployment experience, cloud platforms, APIs, TensorFlow/PyTorch projects and production systems. For every major project, mention the architecture, technologies used and business impact.
📩 How to Apply
📩dharya.aggarwal@deepmindz.co
Interested candidates can DM to Dharya Aggarwal and share updated resume if their experience matches the job requirements.
Interested candidates can DM to Dharya Aggarwal the recruiter or share their updated profile directly with dharya.aggarwal@deepmindz.co. Since this position prefers immediate joiners or candidates available within 15 days, clearly mention your current notice period, total experience and relevant GenAI/LLM experience when applying.
🚀 If you have 4–5 years of hands-on AI experience and are ready to work with Generative AI, LLMs, RAG and modern AI engineering technologies, this Noida opportunity could be a strong next career move.
