Advisory Machine Learning Engineer

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Lenovo is a US$83 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

Please note that the team has moved to a new location. The office is now at 121 Menachem Begin Road, Tel Aviv, 61st floor, in the POINT office complex. As per our office policy, you will be required to visit the site at least three times a week.

Lenovo Digital Trust Lab is seeking a hands-on ML Engineer to join our Hybrid AI Security team. This role focuses on building ML-based AI Guardrails for real-time AI applications, with an emphasis on lightweight and efficient deployment across edge and cloud environments.

You will work at the intersection of machine learning, AI security, and platform engineering — designing models, evaluation frameworks, and end-to-end ML pipelines that help detect unsafe, adversarial, or policy-violating AI interactions, in alignment with Lenovo's Trust, Privacy, and Responsible AI principles.

Job Responsibilities

• Design and maintain ML training and fine-tuning pipelines for LLMs and ML models.
• Develop fine-tuning workflows (e.g., LoRA/PEFT) with auditability, reproducibility, and policy enforcement.
• Implement ML-side security controls: data filtering hooks, dataset labeling, training instrumentation, and detection/mitigation of training-time threats (data poisoning, backdoors, contamination, leakage).
• Integrate model evaluation and testing frameworks focused on security, robustness, and safety into the build phase.
• Collaborate with data scientists and security researchers to embed security and responsible AI capabilities into data preparation and fine-tuning workflows.
• Collaborate with engineers to deploy models on edge devices and cloud environments.
  
  

• 5+ years of experience as an ML Engineer or Applied ML Engineer.
• Strong hands-on experience with Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Hands-on experience training or fine-tuning ML models or LLMs.
• Solid understanding of ML pipelines: data ingestion, preprocessing, training, evaluation, and serving.
• Familiarity with security and Responsible AI concepts (data integrity, bias, robustness).
  
  

• Experience building AI Guardrails and knowledge of LLM fine-tuning techniques (LoRA, QLoRA, PEFT, adapters) and related tooling (Hugging Face, LLaMA Factory, Unsloth).
• Knowledge of training-time attack vectors (data poisoning, backdoor attacks, distribution shift) and experience implementing data scanning, validation, or quality checks in ML pipelines.
• Experience integrating evaluation tools (security, safety, or RAI) into CI/CD or ML pipelines; exposure to secure ML build practices (experiment tracking, versioning, lineage).
• Familiarity with governance or compliance-driven ML workflows; Java/Kotlin/Rust is a bonus.
  
  

• Health Disability Insurance
• Pension/ Retirement Plan
• Meal vouchers
• Employee Referral Bonus
• Lenovo and Motorola Product Discounts
• Employee Assistance Program
• Internal E-learning Development Platform Available for Employees