AI Engineer
- Compensation
- Not disclosed
- Location
- Singapore-Techpt, SGP
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Master’s degree (preferred) in Computer Science, Electrical Engineering, Data Science, or related fields.
- Proven track record of successfully shipping AI solutions from concept to deployment, demonstrating the ability to own the complete lifecycle of ML development.
- Demonstrable experience developing GenAI applications, including Agent-based architectures.
- Strong programming skills in Python.
- Hands-on experience with TensorFlow or PyTorch.
- Hands-on experience curating datasets, and finetuning LLMs.
- Hands-on experience with GenAI development technologies and Agentic AI frameworks (Llamaindex, CrewAI, LangChain, HuggingFace, OpenAI APIs,…).
- Hands-on experience with the complete MLOps workflow, encompassing data processing, training infrastructure, and deployment infrastructure.
Nice to have
- Basic telecom concepts, including RF network architectures, protocols, or telecom-specific data types.
- Experience with telecom network optimization, anomaly detection, or predictive analysis.
- Basics of RF planning, network slicing, Open RAN, or OSS/BSS systems.
- Knowledge of data engineering concepts and technologies (Kafka, Spark Streaming, etc.).
- Contributions to open-source AI projects or active participation in AI communities.
Full description
Summary:
Initiates the design, development, execution and implementation of technology research projects. Investigates the feasibility of applying scientific principles and concepts to potential inventions and products. Plans and executes applied research. Maintains substantial knowledge of state-of-the-art principles and theories, and may contribute to scientific literature and conferences. May participate in development of patent applications. May coordinate interdepartmental activities and research efforts.
Duties & Responsibilities:
VIAVI Solution CTO office seeks a highly motivated AI Engineer passionate about cutting-edge artificial intelligence and telecommunications technologies. This role will focus on the rapid design, development, and deployment of AI-driven solutions, leveraging Generative AI, Large Language Models (LLMs), Agentic AI architectures, Digital twins, and open-source frameworks.
The ideal candidate brings hands-on experience in fast prototyping within native cloud environments and a working understanding of telecom and wireless systems and data analysis.
As part of our innovation team, you will collaborate with CTO leadership, AI solutions architects, Data scientists, and RF and telecom engineers to deliver scalable AI for 6G digital twin solutions that address real-world challenges in the upcoming 6G telecommunications domain, including self-healing networks, automation, intelligent decision-making, customer experience enhancement, and network optimization.
Duties & Responsibilities: Key Responsibilities:
- Conduct the development and fast prototyping of AI-based Digital twin and AI solutions incorporating Agentic AI within telecom workflows.
- Develop and maintain prototypes and MVPs using cloud platforms and on-prem infrastructure.
- Collaborate with telecom subject matter experts to understand network architectures (6G, 5G, Open RAN, OSS/BSS systems), optical networks and translate business needs into AI solutions.
- Design and implement data pipelines for telecom data, including structured and unstructured data.
- Ensure best practices in model evaluation, validation, explain ability, and monitoring.
- Stay current with emerging research, open-source contributions, and industry trends in AI/ML, Generative AI, and Telecom AI applications.
- Develop heterogeneous systems that integrate hardware instruments and monitoring systems with cloud-based AI.
Pre-Requisites / Skills / Experience Requirements: Required Qualifications:
- Master’s degree (preferred) in Computer Science, Electrical Engineering, Data Science, or related fields.
- Proven track record of successfully shipping AI solutions from concept to deployment, demonstrating the ability to own the complete lifecycle of ML development.