Senior AI ML Engineer

Vaisesika Consulting; Bengaluru; Hybrid; INR 3,500,000 - 6,000,000; Full time

Job summary

Vaisesika Consulting seeks a Senior AI/ML Engineer to lead design, development, deployment, and optimization of AI/ML solutions across enterprise use cases. The role requires translating business problems into scalable AI systems and mentoring junior engineers.

You will drive production-grade AI initiatives, collaborating with product and engineering teams to ensure reliable, secure, and compliant ML deployments at scale.

Qualifications

• Strong foundation in ML, DL, statistics, and data science.
• Hands-on experience with Python and ML frameworks.
• Experience deploying models in production.
• Expertise in Generative AI, LLMs, RAG, AI Agents.
• Experience with data processing frameworks and databases.
• Knowledge of cloud platforms and containerization.
• Experience with MLOps and CI/CD for AI systems.

Responsibilities

• Design and develop end-to-end AI/ML solutions for enterprise apps across NLP, CV, analytics, and generative AI.
• Build, fine-tune, and optimize ML/DL models for performance and scalability.
• Develop and deploy LLM-powered apps, AI agents, RAG systems, and workflow automation.
• Design data pipelines, feature engineering, and model training workflows for large-scale data.
• Lead model evaluation, experiments, and hyperparameter tuning.
• Implement MLOps for deployment, monitoring, and versioning.
• Collaborate with cross-functional teams to translate business needs into AI solutions.
• Mentor junior engineers and guide AI architecture and best practices.
• Drive research and adoption of emerging AI tech and methodologies.
• Ensure production systems meet reliability, security, and compliance requirements.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Hugging Face

LangChain

NLP

Generative AI

LLMs

MLOps

Tools

Docker

Kubernetes

Azure

AWS

GCP

Pandas

Spark

SQL

NoSQL

Vector Databases

Job description

Job Summary

We are looking for a highly skilled Senior AI/ML Engineer to lead the design, development, deployment, and optimization of AI/ML solutions across diverse enterprise use cases. The ideal candidate should possess strong expertise in machine learning, deep learning, generative AI, LLMs, and MLOps, with the ability to translate business problems into scalable AI solutions.

This role involves mentoring junior engineers, driving technical decisions, and collaborating closely with product, engineering, and business teams to deliver production-grade AI systems.

Key Responsibilities

• Design and develop end-to-end AI/ML solutions for enterprise applications across NLP, Computer Vision, Predictive Analytics, Recommendation Systems, Generative AI, and Conversational AI domains.
• Build, fine-tune, and optimize machine learning and deep learning models for performance, scalability, and reliability.
• Develop and deploy LLM-powered applications, AI agents, RAG systems, and workflow automation solutions.
• Design data pipelines, feature engineering frameworks, and model training workflows for large-scale datasets.
• Lead model evaluation, experimentation, hyperparameter tuning, and performance optimization initiatives.
• Implement MLOps best practices for model deployment, monitoring, versioning, and continuous improvement.
• Collaborate with cross-functional teams to understand business requirements and translate them into AI-driven solutions.
• Mentor junior engineers and provide technical guidance on AI architecture, coding standards, and best practices.
• Drive research and innovation by evaluating emerging AI technologies, frameworks, and methodologies.
• Ensure production systems meet reliability, scalability, security, and compliance requirements.

Required Skills

• Strong foundation in Machine Learning, Deep Learning, Statistics, and Data Science.
• Hands-on experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, and LangChain.
• Experience building and deploying machine learning models in production environments.
• Expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agent frameworks.
• Experience with data processing frameworks and databases such as Pandas, Spark, SQL, Vector Databases, and NoSQL systems.
• Strong understanding of model optimization, evaluation metrics, and performance tuning.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with containerization and deployment technologies including Docker and Kubernetes.
• Knowledge of MLOps tools and CI/CD practices for AI systems.
• Strong problem-solving, debugging, and analytical skills.

Preferred Skills

• Experience in one or more specialized domains such as NLP, Computer Vision, Speech AI, Time-Series Forecasting, or Recommender Systems.
• Experience building enterprise-grade AI platforms and multi-agent systems.
• Knowledge of distributed training, model quantization, and inference optimization.
• Exposure to edge AI deployment and real-time AI systems.
• Contributions to research publications, patents, or open-source AI projects.
• Experience leading technical teams and mentoring engineers.