Job Description
Role Summary
We are seeking a skilled and hands-on Senior Artificial Intelligence & Machine Learning (AI/ML) Engineer to build and productionize AI solutionsincluding fine-tuning large language models (LLMs), implementing Retrieval-Augmented Generation (RAG) workflows, multi-agent applications and MLOps pipelines.
This role focuses on individual technical contribution and requires close collaboration with solution architects, AIML leads, and fellow engineers to translate business use cases into scalable, secure, cloud-native AI services.
The ideal candidate will bring deep technical expertise across the AI/ML lifecyclefrom prototyping to deploymentwhile contributing to a culture of engineering excellence through peer reviews, documentation, and platform innovation. They will play a critical role in delivering robust, high-performance AI systems in partnership with the broader AI/ML team.
Key Responsibilities
Model Development & Optimization
- Fine-tune foundation models (e.g., GPT-4, Llama 3).
- Implement prompt engineering and basic parameter-efficient tuning (e.g., LoRA).
- Conduct model evaluation for quality, bias, and hallucination; analyze results and suggest improvements.
RAG & Agentic Systems (Exposure, Not Ownership)
- Assist in building RAG pipelines: Participate in integrating and embedding generation, vector stores (e.g., FAISS, pgvector), and retrieval/ranking components.
- Work with multi-agent frameworks (e.g., LangChain, Crew AI)
Production Engineering / MLOps
- Contribute to CI/CD pipelines for model training and deployment (e.g., GitHub Actions, SageMaker Pipelines).
- Help automate monitoring for latency, drift, and cost; assist in lineage tracking (e.g., MLflow).
- Containerize services with Docker and assist in orchestration (e.g., Kubernetes/EKS/GKE)
Data & Feature Engineering
- Build and maintain data pipelines for collection, cleansing, and feature generation (e.g., Airflow, Spark).
- Implement basic data versioning and assist with synthetic data generation as needed
Code Quality & Collaboration
- Participate in design and code reviews.
- Contribute to testing (unit, integration, guardrail/hallucination tests) and documentation.
- Share knowledge through sample notebooks and internal sessions
Security, Compliance, Performance
Follow secure coding and Responsible AI guidelines.
Assist in optimizing inference throughput and cost (e.g., quantization, batching) under guidance.
Ensure SLAs are met and contribute to system auditability
Technology Stack
Programming Languages & Frameworks
- Python (expert)
- JavaScript/Go/TypeScript (nice-to-have)
- Strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch.
- PyTorch, TensorFlow/Keras, Hugging Face Transformers/PEFT, LangChain/LlamaIndex, Ray/PyTorch Lightning, FastAPI/Flask
- Experience working with RESTful APIs, authentication (OAuth, API keys), and pagination
Cloud & DevOps
- Expertise in one or more cloud vendors like AWS, GCP, Azure
- Containers (Docker), Orchestration (Kubernetes, EKS/GKE/AKS)
- MLOps
Databases
- Relational: PostgreSQL, MySQL
- NoSQL: MongoDB / DynamoDB
- Vector Stores: FAISS / pgvector / Pinecone / OpenSearch / Milvus / Weaviate
RAG Components
- Document loaders/parsers, text splitters (recursive/semantic), embeddings (OpenAI, Cohere, Vertex AI), hybrid/BM25 retrievers, rerankers (Cross-Encoder)
Multi-Agent Frameworks
- Crew AI / AutoGen / LangGraph / MetaGPT / Haystack Agents, planning & tool-use patterns
Testing & Quality
- Unit/integration testing (pytest), guardrails
Qualifications
- 710years total software/ML engineering experience, including 3+years delivering ML models or GenAI systems to production.
- Proven track record building and optimising RAG or LLMpowered applications at scale
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow) and in cloudnative deployment (AWS/GCP/Azure).
- Handson experience with vector databases, embeddings, and prompt engineering.
- Experience in regulated industries (Fintech, Healthcare, eCommerce) is a plus.
- Experience with multiagent frameworks (CrewAI, AutoGen, LangGraph).
- Certifications such as AWS CertifiedMachineLearning Specialty / AzureAIEngineer / GoogleProfessionalMachineLearningEngineer.
- Bachelors degree in Computer Science, Data Science, Engineering or related discipline (Masters preferred).
Soft Skills & Leadership Attributes
- Ownership mindset: drives features from design through deployment and monitoring.
- Clear communicator: explains technical tradeoffs to stakeholders, writes concise docs, and updates project artefacts.
- Collaboration & mentorship: pairs with junior engineers, shares knowledge in brownbag sessions, gives constructive PR feedback.
- Continuous learning: tracks latest GenAI research, evaluates new tooling, and proposes incremental improvements.
Job Classification
Industry: IT Services & Consulting
Functional Area / Department: Engineering - Software & QA
Role Category: Software Development
Role: Software Development - Other
Employement Type: Full time
Contact Details:
Company: Aziro
Location(s): Noida, Gurugram
Keyskills:
Tensorflow
Artificial Intelligence
RAG
Aiml
Mlops
LLM
Machine Learning
Python