The role involves designing and deploying machine learning models, ensuring model performance, and optimizing ML infrastructure on GCP, collaborating closely with data engineers and scientists.
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.
What You'll Do
- 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.
- Optimize ML model inference performance to improve latency and cost-efficiency of AI applications.
- 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.
What We're Looking For
- 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.
- Experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with AI orchestration concepts using tools like LangGraph or LangChain is a bonus.
- Bonus experience includes working in gaming, real-time fraud detection, or AI personalization systems and Agentic workflows.
Similar Jobs
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Performs complex semiconductor manufacturing operations independently, serves as a subject matter expert, troubleshoots equipment and process issues, and supports yield, scrap, cycle-time, and productivity improvements. Analyzes manufacturing data, trains production associates, supports engineering evaluations and product introductions, investigates root causes, implements corrective actions, and maintains safety, cleanroom, quality, and operational standards while working rotating 12-hour shifts.
Top Skills:
Cleanroom OperationsHigh-Volume Production OperationsManufacturing EquipmentManufacturing SystemsProcess ControlsSemiconductor Manufacturing
Artificial Intelligence • Hardware • Information Technology • Machine Learning
The GQ NVMQRA Manager oversees a team ensuring SSD product quality and reliability, manages workflows, budgets, and equipment, and supports team development.
Top Skills:
Data AnalysisProject ManagementQuality AssuranceSolid State Drives
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Design, review, and optimize high-reliability power distribution and substation systems for semiconductor fabs. Produce SLDs, sizing calculations, system studies, grounding/earthing, protection coordination, and commissioning support. Integrate SCADA/BMS, ensure compliance with standards, manage vendors/contractors, and support procurement, FAT/SAT, and energization.
Top Skills:
AisArc Flash AssessmentAutocadAutocad ElectricalBimBmsChatgptClaudeCo-PilotEtapFmcsGeneratorsGisHarmonic FiltersLlmsProtection RelaysRevitRmuScadaSkm Power ToolsSwitchgearTransformersUpsVfd
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
