Note: The job is a remote job and is open to candidates in USA. Motorola Mobility, a Lenovo Company, is seeking an AI Infra Engineer to support the delivery of cutting-edge and energy-efficient product offerings. The role involves acting as a bridge between the R&D team and global business teams, localizing and adapting sustainable computing technologies, and representing Lenovo in industry alliances.
Responsibilities
- Lead AI data platform research for large-scale enterprise infrastructure data
- Build prediction and forecasting models for time-series signals, operational metrics, and infrastructure events
- Develop graph-based models to represent entities, dependencies, topology, and causal relationships across infrastructure systems
- Apply Bayesian networks, causal inference, Markov models, and graph neural networks for anomaly detection and root-cause localization
- Use LLMs to automate data cleaning, labeling, metadata generation, document parsing, quality validation, and knowledge extraction
- Optimize large-scale data pipelines for throughput, latency, reliability, scalability, and cost efficiency
- Explore GPU-accelerated data processing and model execution to improve computational efficiency
- Define rigorous evaluation metrics for model accuracy, data quality, system performance, and business impact
- Collaborate with global research, engineering, product, and business teams to deliver platform capabilities
Skills
- Minimum 5 years of hands-on experience in data science, machine learning, applied AI, or AI platform research
- Strong expertise in machine learning, deep learning, probabilistic modeling, causal inference, and time-series forecasting
- Strong experience with graph analytics, knowledge graphs, graph databases, ontology modeling, entity resolution, or graph neural networks
- Strong programming capability in Python, SQL, and distributed data processing
- Hands-on experience with Spark, PySpark, SparkSQL, Hadoop, or cloud-based big data platforms
- Experience with Apache Iceberg, Delta Lake, Hudi, Trino, Presto, or equivalent lakehouse technologies
- Experience with vector databases, embeddings, semantic search, and LLM-based data workflows
- Experience with CUDA programming, GPU-accelerated computing, NVIDIA libraries, kernel optimization, memory optimization, or GPU performance profiling
- Experience with Git, Docker, CI/CD, model deployment, monitoring, and production AI systems
- Master's degree or above in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related technical field
- Strong ability to define ambiguous research problems and deliver measurable technical outcomes
- Strong English communication skills for technical collaboration with global teams
- Preferred additional strengths include AI workload benchmarking, vLLM, SGLang, TensorRT-LLM, publications, patents, open-source contributions, or technical leadership in AI data platforms
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