At Lenovo, we are driven by a bold vision to deliver Smarter Technology for All. Our mission is to develop transformative technologies that foster a more inclusive, trustworthy, and sustainable digital society. Through the design and engineering of the world’s most comprehensive portfolio of smart devices and infrastructure, we are also leading innovation in developing and delivering Hybrid AI solutions that reinvent the way users interact with their fleet of devices. Our Hybrid AI Platform allows for development of AI based solutions that are deployed on Cloud, Agentic AI solutions and Edge solutions on millions of devices. It also gathers data that is analyzed and processed to provide intelligent and innovative solutions with cutting-edge technologies. Join us in shaping the future of intelligent device management and defining the next generation of smarter technology.

About this role

Lenovo Cloud and Software team is seeking an junior AI and Machine Learning Engineer to actively participate in development of AI/ML Platform leading to Platform as a Service model specifically in on-device client applications. This role is also expected to be proficient in data processing techniques, transformation, develop data pipelines to enable consumption by the programmed models. To be successful in this role, candidates must be hands-on developer with rich knowledge of client technologies, TinyML, edge deployment of machine learning models. Proficiency in data lake usage, machine learning and AI concepts using C++/C#, .Net technologies and its foundational library frameworks. This role requires extensive coordination with multiple teams and stakeholders throughout the lifecycle of development. Close collaboration with Architecture team, Product Lifecycle management team, product assurance team, security and others. Release management through Agile processes is a primary responsibility for this role. A successful candidate in this role would have well rounded knowledge of traditional Machine Learning, Data, Cloud and AI concepts.

Primary Skills and Responsibilities

At least 2+ years of relevant experience of full-time working experience in Client (on-device) technologies

Hands on Experience with C++/C#, .Net framework

Strong Data Engineering knowledge with technologies such as Python, TensorFlow (Lite), PySpark

Experience developing small footprint models for on-device usage

Experience with testing technologies for various ML Models

Experience in designing and developing Unsupervised models for clustering, pattern analysis and anomaly detection, forecasting.

Experience in handling Time Series Data, Anomalies detection, Data Correlation techniques

Well versed with model optimization, resources handling, recall and precision tuning, improving performance while maintaining inference quality.

Knowledge of big data processing, transformations, optimized pipeline processing, Lakehouse architecture.

Hands-on development of Solutions in Data Engineering technologies & AI

Participating in daily working sessions, and leading workstreams from planning through execution to closure

Hands on development experience in Python, using related libraries such as Pandas, Pytorch, TensorFlow Lite, Spark

Good understanding of PaaS platforms and associated technologies

Thorough understanding of Agile Development practices, ceremonies

Excellent communication skills

Preferred Skills

Certifications in AWS or equivalent Cloud technologies and AI, ML paths
Microservices architecture knowledge and REST based solutions
Excellent communication, interpersonal, and presentation skills, including clear descriptions and document generation, such as class diagrams, sequence diagrams, and protocol definitions.

Technologies

Proficiency in programming languages such as Python, .Net, C++, TypeScript based languages
Expertise in Machine Learning frameworks such as TensPyTorch, LangChain, LangGraph, R
Client (on-device) technologies/services, Windows Operating system fundamentals
Messaging Protocols such as Kafka, MQTT
SQLLite and NoSQL Databases
Stream processing, Python
Knowledge of multiple Operating Systems such as Windows, Macintosh, Linux, Android, iOS
Algorithmic knowledge of various models and their applicability
SourceControl systems such as Git, BitBucket
Atlassian tools familiarity - JIRA, Confluence, BitBucket