Software Engineer – AI Performance

🔥 0 minutes ago

🇵🇭 Philippines – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DevRev

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 Seed Round on 2022-09

Consulting • Marketing • SaaS

DevRev is a software company that focuses on the development and integration of client-server applications. Despite the technical error message provided, the company aims to streamline operations and enhance client development experiences.

📋 Description

• Participate in structured training to develop expertise in AI benchmarking, profiling, and performance tuning • Build and scale benchmarking infrastructure for evaluating AI systems in enterprise settings • Design agent evaluation pipelines measuring reasoning, accuracy, alignment, and user outcomes • Collaborate with AI and Infrastructure teams to instrument model-serving systems using vLLM, Triton, Ray, or Kubernetes-based deployments • Develop data and telemetry pipelines capturing model performance, latency, and quality • Contribute to DevRev’s open benchmarking frameworks • Work with cross-functional teams to ensure benchmarks reflect real-world customer value and system impact • Help define KPIs for AI-native enterprise software

🎯 Requirements

• 3–10+ years of experience as a Software Engineer in backend, systems, or infrastructure roles • Strong foundation in Python or similar backend languages — Go, Java, C#, or Node.js • Hands-on experience building APIs and cloud-native architectures (AWS, GCP, or Azure; Kubernetes a plus) • Understanding of metrics, profiling, or observability tools (Grafana, Prometheus, ELK, or similar) • Curiosity and commitment to learn AI benchmarking, LLM evaluation, and performance frameworks • Strong analytical and product intuition • Bonus: exposure to vector search, model tuning (LoRA, DPO), or open-source contributions

🏖️ Benefits

• Structured training and mentorship to bridge into AI performance and benchmarking • Structured training track in AI benchmarking, profiling, telemetry, and performance tuning