Senior AI/ML Engineer

Experience: 12+ Years

Job Description

We are looking for an experienced AI/ML Engineer with 12+ years of experience in software engineering, machine learning, artificial intelligence, and data-driven application development. The ideal candidate should have strong hands-on experience with Python, machine learning algorithms, deep learning, NLP, generative AI, and cloud-based ML solutions.

The candidate will be responsible for developing, deploying, and maintaining machine learning solutions and working closely with data scientists, software engineers, product teams, and business stakeholders.

Required Skills

• 12+ years of experience in software engineering, data science, AI/ML, or related technologies.

• Strong programming experience with Python.

• Strong understanding of Machine Learning algorithms, statistics, and predictive modeling.

• Experience with Scikit-learn, Pandas, NumPy, and ML frameworks.

• Hands-on experience with TensorFlow and/or PyTorch.

• Experience developing and deploying Machine Learning models.

• Strong understanding of NLP, text processing, classification, regression, clustering, and recommendation systems.

• Experience with Generative AI, Large Language Models (LLMs), and prompt engineering.

• Knowledge of RAG, embeddings, vector databases, and semantic search.

• Experience working with SQL and NoSQL databases.

• Experience with REST APIs and microservices for integrating ML models with applications.

• Hands-on experience with AWS, Azure, or Google Cloud Platform.

• Experience with Docker, Kubernetes, and CI/CD.

• Knowledge of MLOps, model deployment, monitoring, and model lifecycle management.

• Strong understanding of Git, Agile/Scrum, and SDLC.

Responsibilities

• Design, develop, and deploy machine learning and AI solutions for business requirements.

• Build and optimize predictive and classification models using appropriate ML algorithms.

• Develop data processing and feature engineering pipelines using Python.

• Train, evaluate, validate, and tune machine learning models.

• Develop NLP and Generative AI solutions based on business use cases.

• Work with LLMs, embeddings, vector databases, and RAG-based applications.

• Integrate AI/ML models into enterprise applications using APIs and microservices.

• Deploy and manage ML models in cloud environments.

• Build and maintain MLOps pipelines for model training, deployment, monitoring, and retraining.

• Monitor model performance and address issues related to accuracy, scalability, and reliability.

• Work with data engineers to prepare and transform data required for ML solutions.

• Collaborate with data scientists, software engineers, architects, and product teams.

• Perform code reviews and follow software engineering best practices.

• Troubleshoot production issues and provide root-cause analysis.

• Document technical solutions, model approaches, and deployment processes.

• Mentor junior engineers and provide technical guidance to the team.

Technical Environment

Programming: Python, SQL
ML: Scikit-learn, Pandas, NumPy
Deep Learning: TensorFlow, PyTorch
AI/GenAI: LLMs, NLP, RAG, Prompt Engineering, Embeddings
Databases: PostgreSQL, MySQL, MongoDB, Redis
Vector Databases: Pinecone, FAISS, Weaviate, Milvus
Cloud: AWS, Azure, Google Cloud Platform
DevOps/MLOps: Docker, Kubernetes, Git, Jenkins, CI/CD
APIs: REST, FastAPI, Flask
Data Processing: Spark, PySpark, ETL/ELT

Preferred Skills

• Experience with OpenAI, Azure OpenAI, or other LLM platforms.

• Experience building RAG and agent-based AI applications.

• Knowledge of LangChain or LlamaIndex.

• Experience with ML platforms such as AWS SageMaker, Azure ML, or Vertex AI.

• Knowledge of model serving technologies and ML monitoring.

• Experience with distributed computing and big data technologies.

• Experience with cloud-native application development.

• Strong understanding of AI/ML security, data privacy, and responsible AI practices.

• Experience in Banking, Healthcare, Insurance, Retail, or other enterprise domains.