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Photon

data opportunity

Expert Data Scientist - Gen AI ML - Tampa/Irving/ Mississauga

The role involves building, optimizing, and scaling production-ready Generative AI applications, including designing complex multi-agent systems and implementing advanced RAG pipelines. Key tasks include integrating diverse LLMs, fine-tuning models, and deploying scalable backend services using modern frameworks.

Irving, Texas, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at Photon?

Role Summary:

We are seeking a Generative AI Engineer to build, optimize, and scale

production-ready AI applications. You will design complex multi-agent systems,

implement advanced RAG pipelines, and manage the deployment of both frontier and

local LLMs. The ideal candidate blends deep machine learning expertise with

modern software engineering practices.

Technical Stack:

LLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.

Frameworks: LangChain, LlamaIndex, and Hugging Face.

Orchestration: LangGraph and Multi-Agent Systems (MAS).

Development: Python, FastAPI, and Asynchronous Programming.

RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.

ML/DL: PyTorch, TensorFlow, and Model Fine-tuning.

Deployment: Docker, Production API management, and LLM monitoring.

Tools: Prompt Engineering, Workflow Design, and GenAI Optimization.

Key Responsibilities

  • Develop and orchestrate sophisticated AI workflows using LangGraph and
  • multi-agent architectures.
  • Build and maintain Advanced RAG systems utilizing LlamaIndex and vector
  • databases for high-accuracy retrieval.
  • Integrate and swap diverse LLMs (commercial and open-source) based on
  • performance and cost requirements.
  • Design and deploy high-performance, scalable backend services using FastAPI and
  • Async Python.
  • Fine-tune large language models (LLMs) using PyTorch/TensorFlow to improve
  • domain-specific performance.
  • Optimize GenAI workflows for latency, cost, and reliability using advanced
  • prompt engineering and monitoring tools.
  • Containerize and deploy AI services via Docker to production environments.
  • Required

Qualifications

  • 9+ years of experience ; Hands-on experience building and deploying GenAI
  • applications in a production setting.
  • Strong proficiency in Python and the modern AI library ecosystem (LangChain,
  • LlamaIndex, etc.).
  • Experience with vector search, embedding models, and advanced data retrieval
  • patterns.
  • Knowledge of model fine-tuning techniques and local LLM quantization/hosting.
  • Familiarity with production-grade monitoring, API security, and CI/CD for ML.
  • Compensation, Benefits and Duration
  • Minimum

Compensation

USD 68,000

Maximum

Compensation

USD 240,000

Compensation

is based on actual experience and qualifications of the candidate.

The above is a reasonable and a good faith estimate for the role.

Medical, vision, and dental benefits, 401k retirement plan, variable

pay/incentives, paid time off, and paid holidays are available for full time

employees.

This position is not available for independent contractors

No applications will be considered if received more than 120 days after the date

of this post

Which skills does this role require?

Generative AILLMsRAG PipelinesMulti-Agent SystemsLangChainLlamaIndexHugging FaceLangGraphPythonFastAPIAsynchronous ProgrammingVector DatabasesPyTorchTensorFlowDockerPrompt EngineeringData ScientistMLGeminiOpenAIClaudeLlamaLocal Model DeploymentPostgreSQLModel Fine-tuningProduction API ManagementLLM MonitoringGenAI OptimizationSoftware EngineeringMachine Learning

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Role information can change. Confirm current details on the original application page.

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