About MaxVal:MaxVal started as an IP services company in 2004, with a keen focus on efficiency, cost-effectiveness, and continuous improvement through metrics-based processes. Our focus on these core values led to the tech-enablement of our offerings even before this buzzword became an industry standard. Over the years, MaxVal developed many internal applications to increase our quality and efficiency, and customer satisfaction. As these systems grew and became more sophisticated, we have productized them and offered them to our clients. Today, MaxVal serves over 600 clients across the full IP life cycle with the industry's leading products and services. Our 700 plus employees represent the most IP and tech-savvy individuals in the industry./" At MaxVal, we do the right things and innovate ceaselessly as a winning team to achieve customer success and employee success.Job Responsibilities:Unstructured Data Mining: Design robust web scraping and crawling pipelines (using tools like Playwright or Selenium) to harvest data from the open web. Convert messy, unstructured text into structured knowledge bases.Agentic Workflow Design: Architect and build autonomous AI agents that can break down complex user goals into sub-tasks, execute tool calls (API requests, DB queries) using frameworks like LangGraph.Base NLP Modeling (Supervised & Unsupervised): Build robust Supervised models for text classification, intent detection, and Named Entity Recognition (NER) where LLMs are overkill. Apply Unsupervised techniques (e.g., LDA for topic modeling, K-Means/DBSCAN for clustering) to discover patterns in unlabeled text corpora.RAG (Retrieval-Augmented Generation): Build semantic search solution for context retrieval from millions of data points. Manage vector embedding pipelines. Apply dimensionality reduction techniques (PCA, t-SNE, UMAP) to visualize high-dimensional data or optimize storage/retrieval efficiency in vector databases.LLM Development & Fine-Tuning: Lead the collection, cleaning, and formatting of high-quality instruction datasets (SFT) from raw logs and documents. Select and implement appropriate loss functions (e.g., Contrastive Loss, Triplet Loss) to optimize models for semantic matching.Cloud Deployment (AWS): Deploy scalable AI models and agentic services on AWS using SageMaker, Bedrock, Lambda, and EKS/ECS. Ensure high availability and low latency for real-time inference.Requirements:Required SkillsProgramming: Expert-level Python skills (Pandas, NumPy). Experience with PyTorch/TensorFlow.Data Acquisition: Advanced proficiency in Web Scraping and data mining from unstructured sources (PDFs, HTML, raw text).Agentic AI Exposure: Hands-on experience creating autonomous loops where AI agents use tools (Function Calling) to complete multi-step workflows.LLM Experience: Proven experience building applications powered by LLMs. Deep understanding of Context Windows, Tokenization, Temperature, and Prompt Engineering.Core AI/ML: Strong theoretical and practical foundation in NLP and foundational understanding of Transformers and Deep Learning architectures.RAG (Retrieval-Augmented Generation): Experience building RAG pipelines using Vector Databases (Pinecone, Milvus, Weaviate) to ground LLM responses in company data.Cloud & DevOps: Solid experience with AWS services (Lambda, S3, EC2, CloudWatch). Proficiency with GIT is mandatory for version control and collaboration. Preferred Skills (Nice to Have)Multi-Agent Orchestration: Experience designing systems where multiple specialized agents collaborate to solve a problem.API Development: Strong experience wrapping AI models in FastAPI/Flask for consumption by frontend applications.Experience with Docker/Kubernetes for containerizing AI applications.Basic Qualifications:BS/MS/PhD in Computer Science, Engineering, or a related field.Experience in product development, preferably in SaaS and cloud environments.Experience or understanding of the Intellectual Property (IP) domain is highly desirable.Website Link:
Job Title
Artificial Intelligence Engineer