AI Engineer, MLOps & Production AI

Job Description

Role Overview:As an AI Engineer at i-Genie, you will be responsible for transforming AI prototypes and MVPs into scalable, production-grade products. Your role will involve ensuring the correct DataOps and DevOps foundations are in place, from data ingestion and transformation to final deployment and observability. You will play a crucial part in shaping i-Genies architecture strategy and infrastructure requirements, focusing on optimizing delivery speed, cost, and user experience. This role is not limited to maintaining systems but also involves influencing architectural decisions, redesigning models and processes to eliminate technical debt, and enforcing data and development standards across the team. Your infrastructure will be fundamental in supporting AI solutions used by blue-chip clients to unlock high-stakes consumer insights.Key Responsibilities:- Transform AI prototypes and MVPs into scalable, production-grade products- Ensure DataOps and DevOps foundations are in place for data ingestion, transformation, deployment, and observability- Shape i-Genies architecture strategy and infrastructure requirements- Optimize delivery speed, cost, and user experience- Influence architectural decisions and redesign models and processes to eliminate technical debt- Enforce data and development standards across the team- Support AI solutions used by blue-chip clients to unlock high-stakes consumer insightsQualifications Required:- Minimum of 5 years of experience solving real client problems through data science and data engineering, with a strong focus on NLP- Bachelors degree in Computer Science (science stream)- Proficiency in Python required; PySpark experience strongly preferred- Deep knowledge of Databricks and broad familiarity across the Azure suite- Hands-on experience deploying products into production environments using containers and Kubernetes- Solid understanding of core NLP techniques and common packages such as CoreNLP, OpenNLP, NLTK, Spacy, TextBlob, and 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 plusAdditional Company Details:i-Genie offers:- 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: Short and long-term packages designed to create wealth as the company grows- 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 i-Genie delivers insights at scale- Autonomy: Trust to deliver exceptional work on your terms Role Overview:As an AI Engineer at i-Genie, you will be responsible for transforming AI prototypes and MVPs into scalable, production-grade products. Your role will involve ensuring the correct DataOps and DevOps foundations are in place, from data ingestion and transformation to final deployment and observability. You will play a crucial part in shaping i-Genies architecture strategy and infrastructure requirements, focusing on optimizing delivery speed, cost, and user experience. This role is not limited to maintaining systems but also involves influencing architectural decisions, redesigning models and processes to eliminate technical debt, and enforcing data and development standards across the team. Your infrastructure will be fundamental in supporting AI solutions used by blue-chip clients to unlock high-stakes consumer insights.Key Responsibilities:- Transform AI prototypes and MVPs into scalable, production-grade products- Ensure DataOps and DevOps foundations are in place for data ingestion, transformation, deployment, and observability- Shape i-Genies architecture strategy and infrastructure requirements- Optimize delivery speed, cost, and user experience- Influence architectural decisions and redesign models and processes to eliminate technical debt- Enforce data and development standards across the team- Support AI solutions used by blue-chip clients to unlock high-stakes consumer insightsQualifications Required:- Minimum of 5 years of experience solving real client problems through data science and data engineering, with a strong focus on NLP- Bachelors degree in Computer Science (science stream)- Proficiency in Python required; PySpark experience strongly preferred- Deep knowledge of Databricks and broad familiarity across the Azure suite- Hands-on experience deploying products into production environments using containers and Kubernetes- Solid understanding of core NLP techniques and common packages such as CoreNLP, OpenNLP, NLTK, Spacy, TextBlob, and LLM models- Experience with Large Language Models in a coding context, including pipeline integration and fine-tuning- Working knowledge of non-English t

Keyskills :
PythonSQLNLPNLTKAzureKubernetesPySparkLLMsCoreNLPOpenNLPSpacyTextBlobLLM APIsDatabricks