Immediate Opening For an AI Engineer

Knackforge Soft Solutions; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Knackforge Soft Solutions is seeking a skilled AI/ML Engineer to design and deploy end-to-end AI/ML solutions, from data ingestion to production deployment. You will develop scalable models and data pipelines to address real-world problems.

You will work with Generative AI, LLMs, and prompt engineering, collaborating with cross-functional teams, applying MLOps practices, and ensuring performance, reliability, and security across cloud platforms.

Qualifications

• Strong proficiency in Python and AI/ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with Machine Learning, Deep Learning, and NLP.
• Hands-on experience with Generative AI (LLMs, embeddings, prompt engineering).
• Knowledge of MLOps tools (MLflow, Kubeflow, Azure ML, etc.).
• Knowledge of cloud platforms (Azure, AWS, or GCP).
• Understanding of data engineering concepts and working with large datasets.
• Familiarity with APIs, microservices, and containerization (Docker, Kubernetes).
• Strong problem-solving and analytical skills.

Responsibilities

• Design and deploy end-to-end AI/ML solutions from data ingestion to deployment.
• Build and optimize ML/DL models for real-world use cases.
• Architect scalable, secure AI systems on cloud platforms.
• Work on Generative AI use cases including LLMs and prompt engineering.
• Collaborate with cross-functional teams to translate requirements into AI solutions.
• Develop data pipelines and model lifecycle (MLOps).
• Ensure production performance, scalability, reliability, and monitoring.
• Stay updated with emerging AI trends and evaluate new tools/technologies.
• Mentor junior engineers and guide best practices in AI development.

Skills

Python

ML/NLP knowledge

Generative AI proficiency

Problem solving

Team collaboration

Tools

TensorFlow

PyTorch

Scikit-learn

MLflow

Kubeflow

Azure ML

Docker

Kubernetes

APIs & microservices

Job description

Key Responsibilities

• Design and implement end-to-endAI/ML solutions from data ingestion to deployment.
• Build and optimize machine learning and deep learning models for real-world applications.
• Architectscalable and secureAIsystems using cloud platforms.
• Work on GenerativeAIuse cases including LLMs, promptengineering, and fine-tuning.
• Collaborate with cross-functional teams to translate business requirements intoAIsolutions.
• Develop and manage data pipelines and model lifecycle (MLOps).
• Ensure model performance, scalability, reliability, and monitoring in production.
• Stay updated with emergingAItrends and evaluate new tools/technologies.
• Mentor juniorengineers and guide best practices inAIdevelopment.

Required Skills

• Strong proficiency in Python andAI/ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with Machine Learning, Deep Learning, and NLP.
• Hands-on experience with GenerativeAI(LLMs, embeddings, promptengineering).
• Knowledge of MLOps tools (MLflow, Kubeflow, Azure ML, etc.).
• Knowledgeofcloud platforms (Azure, AWS, or GCP).
• Understanding of dataengineering concepts and working with large datasets.
• Familiarity with APIs, microservices, and containerization (Docker, Kubernetes).
• Strong problem-solving and analytical skills.

Nice to Have

• Certifications inAI/ML or cloud platforms.
• Experience working on production-gradeAIsystems.
• Contributions to open-sourceAIprojects.
• Azure Foundry and Databricks Agent bricks are good to have