Python developer

I8IS - Infiniti Software Solutions; Mississauga; On-site; CAD 120,000 - 160,000; Full time

Job summary

I8IS - Infiniti Software Solutions in Mississauga, Canada seeks a senior AI/ML-focused developer to lead GenAI initiatives. You will architect LLM-powered applications, design RAG pipelines, and drive deployments within enterprise environments.

The role requires hands-on experience with major LLMs, vector databases, and modern MLOps practices, working closely with cross-functional teams in a fast-paced setting.

Qualifications

• 8-10 years of relevant experience in Apps Development or systems analysis role.
• Deep GenAI/LLM foundations and applied AI knowledge.
• Hands-on with leading LLMs and RAG pipelines, model deployment, and MLOps.

Responsibilities

• Build, tune, and deploy LLM-based applications with enterprise integrations.
• Design robust RAG pipelines and prompt strategies.
• Ensure deployment pipelines using CI/CD and container orchestration.

Skills

GenAI foundations

NLP basics

Data science basics

Soft skills

Problem solving

Python

Tools

Google Gemini

OpenAI models

Anthropic Claude

Mistral

Llama

Pinecone

Mongo Atlas

Neo4j

LangChain

LlamaIndex

Vertex AI

Hugging Face

Transformers

PyTorch

TensorFlow

FastAPI

Seaborn

Jenkins

Kubernetes

OpenShift

PG Vector

Job description

• 8-10 years of relevant experience in Apps Development or systems analysis role
  
• Core AI/ML Foundations:
  
• Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
  
• Generative AI & LLM Expertise:
  
• Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
  
• Critical: Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
  
• Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc.
  
• Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates.
  
• Hands-on experience with agentic framework-based use case implementation.
  
• Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features.
  
• Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex.
  
• Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools.
  
• Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval.
  
• Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing.
  
• Deployment & MLOps:
  
• Critical: Hands-on experience deploying GenAI-based models to production environments.
  
• Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines.
  
• Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
  
• Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment.
  
• Soft Skills:
  
• Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems