ML Engineer – Threat Detection Models

Job not on LinkedIn

🔥 11 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 12%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Pragmatike

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

💼 Consulting

📣 Marketing

🎯 Recruiter

Consulting • Marketing • Recruitment

Pragmatike is a remote IT recruitment and staffing company that sources, vets, and places international tech talent for businesses. They provide human-curated matching (not solely AI), technical assessments, and fast placements—claiming qualified specialists can be introduced within 48 hours—while handling onboarding, invoicing and international payroll. Pragmatike serves startups and enterprises with roles like developers, data engineers, mobile and game developers, product managers and specialists, operating across 60+ countries with a large vetted talent pool.

📋 Description

• Design, train, and evaluate threat detectors using classifiers, embedding-based models, fine-tuned LLMs, and rule/ML hybrid approaches • Build and maintain training and evaluation datasets, labeling workflows, and benchmark suites • Track model performance through precision/recall, error analysis, drift, and adversarial robustness • Serve models in production under strict latency requirements • Build inference services in Go and integrate them with gateway and endpoint pipelines • Optimize inference performance and cost through quantization, distillation, batching, and caching • Work with security researchers to turn emerging attack techniques into training data and detection logic • Build and maintain MLOps workflows for reproducible training, model registries, monitoring, and safe model rollouts • Use AI-assisted development workflows for implementation, testing, debugging, and experimentation

🎯 Requirements

• 4+ years of experience building and deploying ML models in production, including NLP or LLM-based classification • Strong Python skills • Experience with PyTorch, Hugging Face Transformers, and scikit-learn • Hands-on experience fine-tuning transformer-based models • Solid Go skills, or strong backend engineering experience with the ability to become productive in Go quickly • Experience with low-latency model serving using ONNX Runtime, TorchServe, Triton, vLLM, or custom serving infrastructure • Strong evaluation discipline, including dataset design, metrics, error analysis, and adversarial testing • Experience with Docker and Kubernetes • Experience with at least one major cloud provider • Fluent English with strong written and verbal communication skills • Comfortable using AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar; this is a must-have • Strong ownership and ability to work independently in a remote-first, distributed environment

🏖️ Benefits

• Remote-first work arrangement • Opportunity to work with a global enterprise cybersecurity company • Work on real-time AI threat detection systems • Ownership of a critical detection workstream • Collaboration with a highly technical, distributed team • AI-assisted development workflows • Inclusive and transparent recruitment process