AI Algorithm Engineer

Lenovo; Selangor; On-site; MYR 70,000 - 100,000; Full time

Job summary

A leading global technology company is seeking a skilled professional to design and develop advanced analytics systems, focusing on operations and anomaly detection. Candidates should have a Bachelor's degree and over 3 years of experience, with proficiency in Python. Familiarity with generative AI technologies and strong communication skills are crucial for this role. Join an innovative team where you will contribute to smarter technology solutions in a dynamic environment in Malaysia.

Qualifications

• 3+ years of experience in related field.
• Familiar with generative AI technologies.
• Experience with anomaly detection and forecasting algorithms.

Responsibilities

• Design and develop Lenovo LHCP system modules.
• Collaborate with product managers and IT operations teams.
• Research and apply technologies to intelligent operations.

Skills

Proficient in Python

Knowledge of Java

Familiar with machine learning algorithms

Strong communication skills

Experience in generative AI

Education

Bachelor's degree or above

Tools

TensorFlow

PyTorch

Hadoop

Spark

Job description

Why Work at Lenovo

Why Work at Lenovo We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$69 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).

Job Responsibilities

• Design and develop Lenovo LHCP system modules, including service health assessment, anomaly detection, capacity estimation, traffic forecasting, risk prediction, and root cause analysis of failures.
• Design and develop algorithms for IT application operations, including time series anomaly detection, log anomaly detection, multi-metric correlation analysis, time series forecasting, and service capacity estimation.
• Construct a general intelligent operations platform for application systems, leveraging the company’s infrastructure to provide foundational datasets, labelled data, data cleaning processes, model training, and runtime frameworks for the above use cases.
• Collaborate with product managers and Lenovo’s internal IT operations teams to build automated operations capabilities applicable to multiple business scenarios.
• Research and apply technologies such as LLMs, rule engines, graph databases, and anomaly detection models to intelligent operations (AIOps) scenarios.

Job Requirements

• Experience: 3+ years.
• Education: Bachelor’s degree or above.
• Proficient in Python; Knowledge of Java or Go is a plus.
• Familiar with common machine learning algorithms and deep learning frameworks such as TensorFlow / PyTorch, including regression, classification, clustering, anomaly detection, time series forecasting, natural language processing and association rules.
• Familiar with generative AI technologies; candidates with hands‑on experience in generative AI application development or large language model fine‑tuning are preferred.
• Experience with anomaly detection, risk prediction, and capacity / traffic forecasting algorithms, or experience in IT operations development, is preferred.
• Experience with big data tools such as Hadoop / Hive / Spark / Flink / Kafka is a plus.
• Strong communication skills, good English reading ability, and a strong spirit of exploration; able to identify cutting‑edge technologies in industry and academia and effectively adapt and apply them in real‑world scenarios.