Data Scientist

Shinebask Technologies LLC.; Auburn Hills (MI); On-site; USD 96,000 - 110,000; Full time

Benefits offered by this job

Hourly pay: $70–$80 per hour

In-person onsite

Job summary

Shinebask Technologies LLC is hiring a Data Scientist in Auburn Hills, MI (onsite) to build and deploy production ML and LLM solutions on AWS. You will provide operational support for production ML/AI systems, implement model governance, and design human-in-the-loop workflows for model oversight and tuning.

The role requires hands-on experience with AWS, LLMs (OpenAI), agentic AI, RAG systems, and front-end surfaces for model outputs, plus strong Python/Java coding and DevSecOps practices.

Qualifications

• Hands-on experience building and deploying ML solutions on AWS.
• Proven experience with LLMs, including OpenAI models/APIs and current knowledge of leading LLM families.
• Hands-on experience building agentic AI systems (multi-agent orchestration, tool use, autonomous workflows).
• Experience building RAG systems, including semantic RAG (embeddings, vector databases, semantic retrieval).
• Deep understanding of data: exploration, quality, feature engineering, and impact on outcomes.
• Strong coding proficiency in Python and Java.
• Experience building front-end interactive applications to expose model outputs (e.g., React, TypeScript).
• Practical experience with Docker/containers and GPU compute for training/inference.
• Experience building and maintaining CI/CD pipelines for ML/AI workloads.
• Working knowledge of DevSecOps practices applied to ML pipelines.
• Familiarity with ML/AI frameworks, including PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex or similar agentic/RAG frameworks.

Responsibilities

• Provide operational support for production ML/AI systems, including monitoring and incident response.
• Implement model governance and monitoring (drift detection, performance tracking, retraining cycles).
• Design human-in-the-loop workflows for model oversight and tuning.
• Apply judgment to select AI/LLM approaches vs traditional methods.
• Define measurable testing and evaluation criteria for model performance and quality.
• Write automated test cases, including AI-assisted test coverage generation.
• Integrate AI governance, legal, and security requirements into development and embed guardrails.
• Build and deploy ML solutions on AWS, including LLM/agentic and RAG systems.
• Support production operations, including DevSecOps and CI-CD for ML/AI workloads.
• Create interactive front-end applications to surface model outputs to end users.

Skills

Python

Java

React

TypeScript

AWS

LLMs

OpenAI APIs

CI/CD

DevSecOps

GPU compute

PyTorch

TensorFlow

Hugging Face

LangChain/LlamaIndex

Tools

Docker

Kubernetes

React

Job description

Shinebask Technologies is hiring a Data Scientist in Auburn Hills, MI (onsite) to build and deploy production ML and LLM solutions on AWS.

Responsibilities

• Provide operational support for production ML/AI systems, including monitoring and incident response
• Implement model governance and monitoring (drift detection, performance tracking, and periodic retraining/tuning cycles)
• Design human-in-the-loop and human-on-the-loop workflows for model oversight, retraining, and tuning
• Apply judgment to select appropriate techniques, including when to use AI/LLM approaches versus traditional methods
• Define measurable testing and evaluation criteria for model performance and quality
• Write automated test cases, including AI-assisted approaches to generate test coverage for model builds
• Integrate AI governance, legal, and security requirements into model development and embed guardrails
• Build and deploy ML solutions on AWS, including LLM/agentic and RAG systems
• Support production operations, including DevSecOps and CI-CD for ML/AI workloads
• Create interactive front-end applications to surface model outputs to end users

Requirements

• Hands-on experience building and deploying ML solutions on AWS
• Proven experience with LLMs, including OpenAI models/APIs and current knowledge of leading LLM model families
• Hands-on experience building agentic AI systems (multi-agent orchestration, tool use, autonomous workflows)
• Experience building RAG systems, including semantic RAG (embeddings, vector databases, semantic retrieval)
• Deep understanding of data: exploration, quality, feature engineering, and impact on outcomes
• Strong coding proficiency in Python and Java
• Experience building front-end interactive applications to expose model outputs (e.g., React, TypeScript, or Java-based UI)
• Practical experience with Docker/containers and GPU compute for training/inference
• Experience building and maintaining CI/CD pipelines for ML/AI workloads
• Working knowledge of DevSecOps practices applied to ML pipelines
• Familiarity with ML/AI frameworks, including (as examples) PyTorch, TensorFlow, Hugging Face, and LangChain/LlamaIndex or similar agentic/RAG frameworks

Technologies

• AWS
• OpenAI models/APIs
• Python
• Java
• React
• TypeScript
• Java-based UI
• Docker, containers
• GPU compute
• CI/CD pipelines
• DevSecOps
• PyTorch
• TensorFlow
• Hugging Face
• LangChain
• LlamaIndex
• GCP
• Azure ML/AI services

Benefits

• Pay: $70.00 - $80.00 per hour
• Work Location: In person

Preferred Qualifications

• Working knowledge of GCP and Azure ML/AI services
• Experience with responsible AI toolkits (bias/fairness testing, model explainability)
• Certifications in AWS ML/AI or relevant cloud platforms