Machine Learning Engineer

This is a fully remote position, open to applicants in United States, +3 more locations.

📋 Description

• Design, train, refine, and assess machine learning models aimed at security detection applications.

• Create lightweight, high-performance models that are optimized for low latency, reduced inference costs, high throughput, and operational reliability.

• Develop fine-tuning pipelines for large language models (LLMs) and smaller transformer-based architectures.

• Explore techniques such as distillation, quantization, pruning, retrieval augmentation, and parameter-efficient fine-tuning methods including LoRA and adapters.

• Enhance detection accuracy while reducing false positives and negatives.

• Establish scalable ML infrastructure and production-ready inference pipelines.

• Collaborate with security researchers to convert detection logic into ML-enhanced systems.

• Assess and optimize model performance considering quality, speed, memory usage, and cost.

• Contribute to data engineering and labeling processes for supervised training.

• Monitor deployed models and continuously enhance their robustness and reliability.

⛳️ Requirements

• A minimum of 2 years of experience in Machine Learning Engineering or Applied AI.

• Proven experience in building and deploying ML systems in production environments.

• Familiarity with fine-tuning transformer models or LLMs.

• Proficient in Python programming.

• Experience with contemporary ML frameworks like PyTorch and Hugging Face; knowledge of TensorFlow is a plus.

• Ability to optimize models for inference efficiency and scalability.

• Strong understanding of model evaluation, experimentation, data pipelines, and distributed training.

• Experience in deploying models within cloud or containerized settings.

• Strong foundation in software engineering principles and a production-oriented mindset.

🏝️ Benefits

• Competitive salary.

• Comprehensive benefits package.

• Flexible working environment.

• Annual wellness and community outreach days.

• Continuous recognition for your contributions.

• Opportunities for global collaboration and networking.

• Flexible time-off policy.

• Holistic well-being program.

• Two paid Wellbeing Days annually.

• Two paid Volunteer Days each year.

• Option for a three-week Work from Anywhere arrangement.

• Potential for variable compensation and/or equity options.