Senior MLOps Engineer

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🔥 34 minutes ago

🇦🇪 United Arab Emirates (UAE) – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

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Fortytwo

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

Artificial Intelligence • B2B • SaaS

Fortytwo is a decentralized AI network that allows anyone to contribute to planetary-scale intelligence by running AI models on everyday hardware. The platform enables users to participate in a community-driven AI ecosystem where multiple consumer devices collaborate to enhance the speed and accuracy of AI inference. By collectively processing user requests, Fortytwo's nodes facilitate smarter, faster, and more efficient AI solutions, operating without centralized control to ensure openness and accessibility.

📋 Description

• Deploy scalable, production-ready ML services with optimized infrastructure and auto-scaling Kubernetes clusters • Optimize GPU resources using MIG (Multi-Instance GPU) and NOS (Node Offloading System) • Manage cloud storage such as S3 for high availability and performance • Integrate LoRA and model merging workflows into ML processes • Work with and adapt state-of-the-art ML codebases to organizational needs • Deploy and manage LLMs, SLMs, and LMMs • Serve ML models using Triton Inference Server • Use vLLM, TGI, and other state-of-the-art serving frameworks • Optimize models with ONNX and TensorRT • Develop RAG systems integrating spreadsheet, math, and compiler processors • Set up monitoring and logging using Grafana, Prometheus, Loki, Elasticsearch, and OpenSearch • Write and maintain CI/CD pipelines using GitHub Actions • Create Helm templates for rapid Kubernetes node deployment • Automate workflows using cron jobs and Airflow DAGs

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field • Proficiency in Kubernetes, Helm, and containerization technologies • Experience with GPU optimization (MIG, NOS) and cloud platforms (AWS, GCP, Azure) • Strong knowledge of monitoring tools (Grafana, Prometheus) and scripting languages (Python, Bash) • Hands-on experience with CI/CD tools and workflow management systems • Familiarity with Triton Inference Server, ONNX, and TensorRT for model serving and optimization • Preferred: 5+ years of experience in MLOps or ML engineering roles • Preferred: Experience with advanced ML techniques, such as multi-sampling and dynamic temperatures • Preferred: Knowledge of distributed training and large model fine-tuning • Preferred: Proficiency in Go or Rust programming languages • Preferred: Experience designing and implementing highly secure MLOps pipelines, including secure model deployment and data encryption

🏖️ Benefits

• Engage in meaningful AI research • Work on decentralized inference, multi-agent systems, and efficient model deployment • Build scalable and sustainable AI systems • Collaborate with a highly technical team • Autonomy in a research-driven environment • Opportunity to work on foundational AI challenges

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