AI Engineer, MLOps & Production AI
Kratos Growth · Remote · remote · Posted 26d ago
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About this role
We are hiring an AI Engineer, MLOps & Production AI
Our AI-powered consumer insights platform is used by global brands such as Coca-Cola, Unilever, and Bayer.
We are upending the multi-billion dollar consumer survey industry with modern AI and NLP techniques that gather rich data from the billions of Google Searches, social media and video posts, and product reviews online.
Job Description
As an AI Engineer, you'll transform AI prototypes and MVPs into scalable, production grade products , ensuring the right DataOps and DevOps foundations are in place, from data ingestion and transformation through to final deployment and observability.
You'll play a central role in shaping the company's architecture strategy and infrastructure requirements, optimizing for delivery speed, cost, and user experience.
This isn't just about keeping systems running. You'll influence real architectural decisions, redesign models and processes to eliminate technical debt, and enforce data and development standards across the team.
Your infrastructure will directly underpin AI solutions used by blue-chip clients to unlock high stakes consumer insights.
What You'll Work With
Core Stack: Python, PySpark, SQL
AI/ML: LLMs, NLP pipelines, model fine tuning, AI prototype productionization
NLP Libraries: CoreNLP, OpenNLP, NLTK, Spacy, TextBlob, LLM APIs
Cloud & Infrastructure: Azure suite, Databricks, containers, Kubernetes
Collaboration: Work closely with data scientists, data engineers, and product teams
Qualifications: What We're Looking For
- 5+ years solving real client problems through data science and data engineering, with strong NLP focus
- Computer Science degree (science stream)
- Python proficiency required; PySpark experience strongly preferred, at minimum, Python mastery with a working understanding of Spark
- Deep knowledge of Databricks and broad familiarity across the Azure suite
- Hands-on experience pushing products into production environments (containers, Kubernetes)
- Solid grounding in core NLP techniques and common packages (CoreNLP, OpenNLP, NLTK, Spacy, TextBlob, LLM models)
- Experience with Large Language Models in a coding context, including pipeline integration and fine-tuning
- Working knowledge of non-English text data processing
- SQL skills are a plus
What We Offer
Global remote work: Work from wherever you do your best thinking
Ownership & impact: Shape the architecture powering AI products used by Fortune 100 companies
Competitive compensation: Long term packages
Cutting, edge problems: Real, world production challenges at the intersection of MLOps, LLMs, and NLP
Direct business impact: Your infrastructure decisions will determine how fast and how well we deliver insights at scale
Autonomy: We trust you to deliver exceptional work on your terms
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