Machine Learning Engineer

🔥 15 hours ago

🌐 United States, India, +1 more countries – Remote

🇺🇸 United States – Remote 🇮🇳 India – Remote 🇬🇷 Greece – Remote

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

🚫👨‍🎓 No degree required

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👻 Ghost score 10%

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Proofpoint

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2002

🔒 Cybersecurity

🏢 Enterprise

🔐 Security

💰 $28M Series F on 2008-02

Cybersecurity • Enterprise • Security

Proofpoint is a company that specializes in cybersecurity solutions, particularly focused on protecting enterprise users from targeted phishing emails and other threats. Their Targeted Attack Protection (TAP) product is designed to provide advanced threat security by checking the safety of websites linked in emails. If a site is deemed safe, users are redirected to the original web destination; if not, access is blocked to prevent exposure to malware. Proofpoint ensures secure email communications within organizations.

📋 Description

• Design, train, fine-tune, and evaluate machine learning models for security detection use cases • Build lightweight, high-performance models optimized for low latency, low inference cost, high throughput, and operational reliability • Develop fine-tuning pipelines for LLMs and smaller transformer-based models • Experiment with distillation, quantization, pruning, retrieval augmentation, and parameter-efficient fine-tuning techniques such as LoRA and adapters • Improve detection quality while minimizing false positives and false negatives • Build scalable ML infrastructure and production inference pipelines • Partner with security researchers to transform detection logic into ML-powered systems • Measure and optimize model performance across quality, speed, memory footprint, and cost • Contribute to data engineering and labeling workflows for supervised training • Monitor production models and continuously improve robustness and reliability

🎯 Requirements

• 2+ years of experience in Machine Learning Engineering or Applied AI • Strong experience building and deploying ML systems in production • Experience fine-tuning transformer models or LLMs • Strong Python engineering skills • Experience with modern ML frameworks such as PyTorch and Hugging Face; TensorFlow optional • Experience optimizing models for inference efficiency and scale • Solid understanding of model evaluation, experimentation, data pipelines, and distributed training • Experience deploying models in cloud or containerized environments • Strong software engineering fundamentals and production mindset

🏖️ Benefits

• Competitive compensation • Comprehensive benefits • Flexible work environment • Annual wellness and community outreach days • Always on recognition for your contributions • Global collaboration and networking opportunities • Flexible time off • Comprehensive well-being program • Two paid Wellbeing Days per year • Two paid Volunteer Days per year • Three-week Work from Anywhere option • Variable compensation and/or equity may be available