job description
Join Patsnap as a Senior Machine Learning Engineer (AI Agent) and lead the development of cutting-edge AI solutions that transform how businesses leverage data. In this role, youâll design, implement, and optimize advanced NLP models and machine learning algorithms to extract actionable insights from vast structured and unstructured datasets. Your expertise in data processing, Named Entity Recognition (NER), and AI-driven automation will drive innovation in our AI agent systems, empowering global enterprises with intelligent decision-making tools.
Based in the vibrant and inspiring environment of Bali, Indonesia, youâll collaborate with a world-class team of engineers, data scientists, and product leaders to push the boundaries of whatâs possible in AI. Whether youâre refining large language models, enhancing semantic search capabilities, or building scalable ML pipelines, your work will have a direct impact on Patsnapâs mission to revolutionize data intelligence.
We offer a competitive salary, flexible remote work options, and the opportunity to grow in a dynamic, fast-paced industry. If youâre passionate about AI, NLP, and machine learning and thrive in a collaborative, innovation-driven culture, weâd love to hear from you.
Responsibility
- Design, develop, and deploy advanced NLP models for tasks such as text classification, NER, and semantic analysis to extract insights from unstructured data.
- Lead the architecture and optimization of machine learning pipelines for large-scale data processing, ensuring efficiency and scalability.
- Collaborate with cross-functional teams to integrate AI agents into Patsnapâs core products, enhancing automation and intelligence.
- Research and implement state-of-the-art ML techniques, including transformers, LLMs, and reinforcement learning, to improve model performance.
- Develop and maintain data preprocessing frameworks to clean, normalize, and augment datasets for training and inference.
- Monitor, evaluate, and fine-tune models in production, ensuring high accuracy, low latency, and robustness.
- Mentor junior engineers and contribute to best practices in MLOps, model versioning, and deployment strategies.
- Stay ahead of industry trends in AI, NLP, and generative models to drive continuous innovation.
Qualifications
- 5+ years of experience in Machine Learning, NLP, or AI engineering, with a proven track record of deploying models in production.
- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Deep understanding of NLP techniques (e.g., tokenization, embeddings, attention mechanisms) and libraries (e.g., spaCy, NLTK).
- Experience with large-scale data processing tools (e.g., Spark, Dask) and cloud platforms (e.g., AWS, GCP, Azure).
- Familiarity with MLOps tools (e.g., MLflow, Kubeflow) and CI/CD pipelines for model deployment.
- Solid background in statistics, linear algebra, and probability as they apply to machine learning.
- Experience with vector databases, RAG systems, or AI agent frameworks is a plus.
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.