Lenovo · 3 hours ago
AI Model Engineer
North Carolina, United States
Full-time
Onsite
Entry, Mid Level
2+ years expLenovo is a global technology powerhouse focused on delivering Smarter Technology for All. They are seeking a highly motivated Foundation Model Engineer to contribute to the design, development, and exploration of next-generation AI systems, focusing on adapting and improving foundation models for real products.
ComputerConsumer ElectronicsElectronicsHardwareMobileWearables
Responsibilities
Fine-tune and adapt foundation models Design and run fine-tuning and parameter-efficient training (e.g., LoRA, adapters, low-rank methods) for LLMs and related models to support specific products and domains
Implement post-training pipelines Build and maintain pipelines for instruction tuning, preference optimization (e.g., RLHF, DPO), and tool-use training to improve helpfulness, safety, and controllability
Data curation and labeling strategy Work on dataset creation, filtering, deduplication, and labeling strategies; collaborate with data and annotation teams to define high-quality training and evaluation sets
Optimize training performance Profile and optimize training jobs for throughput and cost efficiency across GPUs/accelerators (batching, sharding, mixed precision, memory optimization)
Model evaluation benchmarking Design and run evaluation suites (automatic metrics + human evals), analyze regressions, and compare model variants across internal and external benchmarks
Production readiness Partner with infra and product teams to move trained checkpoints into production, including versioning, rollout strategies, and monitoring model behavior in the wild
Stay current with the field Track advances in model architectures, optimization methods, and training techniques; propose and run experiments to bring relevant ideas into the stack
Qualification
Required
2+ years of industry experience in ML, applied research, or highly relevant internships/research roles
Master's degree or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
Strong programming skills in Python
Deep familiarity with PyTorch, TensorFlow, or JAX
Solid understanding of deep learning fundamentals: optimization, regularization, initialization, distributed training basics
Hands-on experience training or fine-tuning large models (not just calling APIs): e.g., language models, vision-language models, or similar
Comfort working with training pipelines, experiment tracking, and model checkpoints
Experience building datasets for training/eval and running structured experiments
Ability to analyze results, understand failures, and iterate quickly
Preferred
Experience with LLM-specific training techniques (instruction tuning, tool-use tuning, chat models)
Experience with RLHF or preference-based learning (e.g., reward models, DPO, PPO-style training)
Familiarity with distributed training frameworks (e.g., DeepSpeed, FSDP, Megatron, XLA, custom sharding strategies)
Prior work on safety, bias, robustness, or alignment of large models
Publications, open-source contributions, or strong public projects in large-scale ML
Company
Lenovo
Lenovo Group is a computer technology company that manufactures personal computers, smartphones, televisions, and wearable devices.
10001+ employees
H1B Sponsorship
Lenovo has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (76)
2024 (52)
2023 (75)
2022 (82)
2021 (58)
2020 (67)
Funding
Current Stage
Public CompanyTotal Funding
$3.35BKey Investors
Alat
2025-01-08Post Ipo Debt· $2B
2024-04-01Post Ipo Debt· $500M
2017-10-03Post Ipo Equity· $500M
Leadership Team
Yang Yuanqing
Chairman & CEO
Greg Huff
CTO, CSO, and SVP of Development, Quality, and Customer Care, Infrastructure Solutions Group
Recent News
2025-12-31
2025-12-31
2025-12-31
Company data provided by crunchbase