Full Stack AI Engineer

Job Description

AI FULL STACK ENGINEER at MOTOR INFORMATION SYSTEMS

MOTOR Information Systems, an operating group of Hearst and a leading automotive data supplier, is actively seeking a team of enthusiastic, creative, and driven AI Engineers.

The Opportunity:
We are assembling a team of visionary technologists - individuals who thrive at the intersection of creativity and execution. We seek engineers who don't just follow trends but actively shape them, experimenting relentlessly, embracing intelligent risk-taking, and iterating with purpose. If you are driven by the rapid evolution of AI, possess an insatiable curiosity for generative models, and have a track record of turning cutting-edge research into real-world applications, we want you.

This role is for those who don't wait for direction but instead explore, prototype, and push boundaries autonomously. You'll work alongside a team that values self-directed innovation, where failing fast is a stepping-stone to breakthroughs.

Role Summary

As a Full Stack AI Engineer, you will architect, build, and deploy next-generation AI applications powered by the latest advancements in LLMs (GPT-4, Gemini, Claude, Llama, Mistral), autonomous agents, and multimodal generative systems. You'll bridge the gap between research and production-designing scalable, high-impact solutions that redefine how businesses and users interact with AI. Beyond implementation, you'll influence the trajectory of our AI strategy, staying ahead of emerging frameworks, optimizing model performance, and ensuring our stack remains at the forefront of the industry.

Key Responsibilities

• AI Systems Design & Development - Architect and deploy robust, scalable AI solutions leveraging LLMs, RAG, fine-tuning, and agentic workflows for NLP tasks (text generation, summarization, Q&A, etc.).
• Performance Optimization - Continuously refine model efficiency, latency, and accuracy using quantization, distillation, and cutting-edge inference techniques.
• Full-Stack Integration - Seamlessly embed AI capabilities into end-to-end applications, ensuring smooth interoperability between frontend, backend, and cloud infrastructure.
• Rapid Prototyping & Experimentation - Test bold hypotheses, iterate quickly, and pivot intelligently based on empirical results.
• Production Deployment & MLOps - Containerize, deploy, and monitor AI systems in cloud environments (AWS/Azure) with CI/CD pipelines.
• Research & Thought Leadership - Stay ahead of the curve by evaluating emerging technologies (e.g., Gemini 1.5, Mistral, open-source alternatives) and advocating for adoption where impactful.

Who You Are

• A Builder - You've developed multiple generative AI projects in the past 18 months, leveraging frameworks like LangChain, LlamaIndex, AutoGen, and/or DSPy.
• A Technical Polymath - Proficient in Python, SQL, PyTorch/TensorFlow, and big data tools (PySpark, Pandas, Polars) with hands-on cloud experience (AWS Sagemaker, Azure AI, GCP Vertex).
• An Autodidact - You learn voraciously, whether through research papers, hackathons, or open-source contributions.
  A Pragmatic Innovator - You balance bleeding-edge experimentation with production-grade engineering rigor.
• A Collaborator - You thrive in cross-functional teams, translating complex AI concepts into actionable insights for stakeholders.

Must have Qualifications and Skills

• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
• At least 5 years of experience in software development, preferably in AI or natural language processing.
• Excellent communication, collaboration, and problem-solving skills.
• Must be proficient in Python and SQL.
• Hands-on experience with large language models and agents such as GPT-4, Gemini, Llama, Mistral and their applications.
• Strong knowledge of natural language processing concepts and techniques such as tokenization, embedding, attention, transformers, etc.
• Experience with agile development methodologies and tools such as Azure DevOps or Git.
• Excellent communication, collaboration, and problem-solving skills.

Preferred Qualifications & Skillset

• Master's in computer science or AI related discipline from an accredited school
• Experience building Delta live pipelines in Databricks as well as working in serverless environments
• Experience deploying distributed models in EKS as well as optimization with Karpenter or similar tools
• Practical experience and understanding of selective fine-tuning techniques (LORA and/or QLORA) and methods such as RLHF, RFT etc.

Why Join?

• Work with state-of-the-art models before they hit mainstream adoption.
• A culture that rewards initiative-no bureaucracy, just high-impact work.
• Flexibility to explore moonshot ideas with resources to back them.

If you're ready to build the future of AI, not just follow it, apply now

EEO EMPLOYER