Machine Learning Engineer with an Agentic Focus

High 5 Games; India; Remote; INR 1,200,000 - 2,400,000; Full time

Job summary

High 5 Games is seeking a Machine Learning Engineer to design, build, and scale ML operations across our GCP-based platform serving millions of players worldwide.

You will work with data scientists, ML Ops, and data engineers to automate workflows, monitor models, and ensure reliable lifecycle management from research to production. Proficiency in Python, ML frameworks, and cloud data services is required, with bonus points for LangGraph/LangChain and gaming domain experience.

Qualifications

• 1+ years of experience as an ML Engineer, with production ML deployment.

Responsibilities

• Design, develop, and deploy ML models and solutions with orchestration and lifecycle management.
• Build scalable data pipelines for real-time and batch processing.
• Develop monitoring strategies for model drift, logging, and observability.
• Optimize ML model inference latency and cost-efficiency.
• Ensure reliability and security of ML data infrastructure.
• Troubleshoot issues impacting ML models and production AI system.
• Ensure data governance and security for real-money gaming.

Skills

ML in production

GCP expertise

Docker & Kubernetes

Python

ML frameworks

LangGraph/LangChain

Gaming domain

Model monitoring

Tools

Docker

Kubernetes

GKE

BigQuery

Dataflow

Vertex AI

Cloud Run

Pub/Sub

Composer (Airflow)

LangGraph

LangChain

TensorFlow

PyTorch

scikit-learn

Job description

WhatYou'llDo

We are looking for a Machine Leaning Engineer (MLE) to design, build, and optimize our machine learning operation. You will play a crucial role in scaling AI models from research to production, ensuring smooth model deployment, monitoring, and lifecycle management across our Google Cloud Platform (GCP) infrastructure. You'll work closely with data scientists, ML Ops, and data engineers to automate workflows, improve model performance, and ensure reliability for our AI that serves millions of players worldwide.

• Design, develop, and deploy machine learning models and solutions, leveraging tools such as LangGraph and MLflow for orchestration and lifecycle management.
• Collaborate on building and maintaining scalable data and feature pipeline infrastructure for real time and batch processing using tools like BigQuery, BigTable, Dataflow, Composer(Airflow), PubSub, and Cloud Run to support ML model training and inference.
• Develop and implement robust strategies for model monitoring and observability to detect model drift, bias, and performance degradation, leveraging tools like Vertex AI Model Monitoring and custom dashboards.
• OptimizeMLmodelinferenceperformancetoimprovelatencyandcost-efficiencyofAIapplications.
• Ensure the overall reliability, performance, and scalability of the ML models and data infrastructure platform, including proactive identification and resolution of issues related to model performance and data quality.
• Troubleshoot and resolve complex issues impacting ML models, data pipelines, and production AI system.
• Ensure AI/ML models and workflows meet data governance, security, and compliance requirements, specifically for real-money gaming.

WhatWe'reLookingFor

• 1+ years of experience as an ML Engineer, with a focus on developing and deploying machine learning models in production environments.
• Strong experience in Google Cloud Platform (GCP), including services relevant to ML and data infrastructure such as BigQuery, Dataflow, Vertex AI, Cloud Run, and Pub/Sub and Composer (Airflow).
• Solid grasp of containerization (Docker, Kubernetes) and experience with Kubernetes orchestration platforms like GKE for deploying ML services.
• Experience building and deploying scalable data pipelines and machine learning models in production environments.
• Understanding of model monitoring, logging, and observability best practices for ML models and applications.
• ExperienceinPythonandMLframeworks(e.g.,TensorFlow,PyTorch,scikit-learn).
• FamiliaritywithAIorchestrationconceptsusingtoolslikeLangGraphorLangChainisabonus.
• Bonus experience includes working in gaming, real-time fraud detection, or AI personalization systems and Agentic workflows.