Ai Ml Engineer

KnowledgeWorks Global (KGL); Chhalera, Mumbai; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

KnowledgeWorks Global (KGL) is seeking an experienced AI/ML engineer to design, develop, and deploy Generative AI and LLM-based solutions. You will fine-tune models, engineer prompts, and build modular AI apps using LangChain and related tools.

Collaboration with data engineers, product managers, and software engineers will be essential to deliver end-to-end AI solutions. You will stay current with AI/ML research, implement MLOps for production models, and champion responsible AI practices

Qualifications

• 3+ years of experience in software development (Python preferred; familiarity with Java, C#, or Node.js a plus).
• 3+ years of hands-on experience in Generative AI and LLM-based development.
• Strong knowledge of AI/ML fundamentals including NLP, deep learning, embeddings, and transformers.
• Experience with LLMs (e.g., OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar).
• Knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks.
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI services (Bedrock, VertexAI, Azure OpenAI).
• Knowledge of MLOps tools (MLflow, Kubeflow, Weights & Biases) for model lifecycle management.
• Strong problem-solving, analytical, and communication skills.

Responsibilities

• Design, develop, and deploy AI/ML solutions with a focus on Generative AI and LLMs.
• Fine-tune, prompt-engineer, and optimize LLMs for domain-specific tasks.
• Leverage frameworks such as LangChain, LlamaIndex, or Haystack for modular AI apps.
• Integrate LLMs with APIs, databases, vector stores, and enterprise apps.
• Evaluate and implement model deployment strategies (on-prem, cloud, serverless, or containers).
• Collaborate with data engineers, product managers, and software engineers to deliver end-to-end AI solutions.
• Stay updated with AI/ML and GenAI research and propose adoption of new tech.
• Implement MLOps best practices for continuous training, deployment, and monitoring.
• Ensure responsible AI practices focusing on bias, privacy, and compliance.

Skills

Python

LLMs

AI/ML fundamentals

NLP

Transformers

problem-solving

communication

Tools

LangChain

LlamaIndex

Haystack

Pinecone

Weaviate

Milvus

FAISS

Chroma

AWS

Azure

GCP

Bedrock

VertexAI

Azure OpenAI

MLflow

Kubeflow

Weights & Biases

Job description

Key Responsibilities

• Design, develop, and deploy AI/ML solutions with a focus on Generative AI and LLMs.
• Fine-tune, prompt-engineer, and optimize LLMs for domain-specific tasks.
• Leverage frameworks such as LangChain, LlamaIndex, or similar for building modular AI applications.
• Integrate LLMs with APIs, databases, vector stores, and enterprise applications.
• Evaluate and implement model deployment strategies (on-prem, cloud, serverless, or containerized environments).
• Collaborate with cross-functional teams (data engineers, product managers, software engineers) to deliver end-to-end AI solutions.
• Stay updated with the latest advancements in AI, ML, and GenAI research and propose adoption of new technologies.
• Implement MLOps best practices for continuous training, deployment, and monitoring of models in production.
• Ensure responsible AI practices, focusing on bias mitigation, data privacy, and compliance.

Required Qualifications

• 3+ years of experience in software development (Python preferred; familiarity with Java, C#, or Node.js a plus).
• 3+ years of hands-on experience in Generative AI and LLM-based development.
• Strong knowledge of AI/ML fundamentals including NLP, deep learning, embeddings, and transformers.
• Experience with LLMs (e.g., OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar).
• Knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks.
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI services (Bedrock, VertexAI, Azure OpenAI).
• Knowledge of MLOps tools (MLflow, Kubeflow, Weights & Biases) for model lifecycle management.
• Strong problem-solving, analytical, and communication skills.