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# Applied AI Scientist

- **Company:** Ova Technologies
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Computer Vision, Microsoft Azure, Cloud Computing, Distributed Computing Environment, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Performance Tuning, Tensorflow, Standard Sql, Software Engineering, Unstructured Data, Reinforcement Learning, Pinecone, Google Cloud, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Llamaindex, Generative AI, Agentic-AI, Git, Fastapi, AI Platforms, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Weaviate, Milvus, Machine Learning Operations, FAISS, Api Design, Google Gemini, Restful APIs, Docker, ChromaDB
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/8f309243-7828-4877-8d84-d51dd5cf89ab/applied-ai-scientist

## About the Role

* Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, or a related field.
 * 3 8 years of experience in AI research, applied machine learning, or data science.
 * Strong knowledge of machine learning, deep learning, NLP, computer vision, and statistical modeling.
 * Experience developing and deploying production AI applications.
 * Proficiency in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
 * Hands-on experience with LLMs, prompt engineering, embeddings, vector databases, and RAG architectures.
 * Strong understanding of experimental design, model evaluation, and performance optimization.
 * Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications

 * Experience with multimodal AI, reinforcement learning, or agentic AI systems.
 * Familiarity with distributed training and large-scale model deployment.
 * Experience with cloud AI platforms and MLOps practices.
 * Publications, patents, or contributions to open-source AI projects.
 * Experience in industries such as healthcare, finance, manufacturing, retail, or telecommunications.
 * Professional certifications in AI, machine learning, or cloud technologies.

Technical Skills

 * Python
 * SQL
 * Machine Learning
 * Deep Learning
 * Natural Language Processing (NLP)
 * Computer Vision
 * Large Language Models (LLMs)
 * Generative AI
 * Prompt Engineering
 * Retrieval-Augmented Generation (RAG)
 * AI Agents
 * Reinforcement Learning (preferred)
 * PyTorch
 * TensorFlow
 * Scikit-learn
 * Hugging Face Transformers
 * LangChain
 * LlamaIndex
 * Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Milvus)
 * OpenAI API
 * Google Gemini API
 * Anthropic API
 * FastAPI
 * Docker
 * Kubernetes
 * Git
 * MLflow
 * REST APIs
 * AWS, Microsoft Azure, or Google Cloud

Soft Skills

 * Research and analytical thinking
 * Problem-solving
 * Innovation and creativity
 * Communication and presentation
 * Cross-functional collaboration
 * Critical thinking
 * Project management
 * Adaptability
 * Continuous learning

## Description

We are seeking an Applied AI Scientist to research, design, develop, and deploy AI solutions that address real-world business challenges. The ideal candidate combines expertise in machine learning, deep learning, natural language processing (NLP), computer vision, and generative AI with strong problem-solving and software engineering skills. This role involves translating research into production-ready AI applications, collaborating with cross-functional teams, and driving innovation across AI initiatives., * Research, design, and develop AI and machine learning solutions for business and product use cases.

 * Build, train, fine-tune, evaluate, and optimize machine learning and deep learning models.
 * Develop applications using large language models (LLMs), multimodal AI, and generative AI technologies.
 * Design and implement Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation solutions.
 * Conduct experiments to evaluate model accuracy, robustness, scalability, and business impact.
 * Analyze structured and unstructured data to derive insights and improve model performance.
 * Collaborate with data scientists, AI engineers, software developers, product managers, and business stakeholders.
 * Translate research findings into scalable, production-ready AI systems.
 * Implement model monitoring, evaluation, and continuous improvement processes.
 * Publish technical documentation, research findings, and reusable AI assets where appropriate.
 * Stay current with advancements in AI, foundation models, reinforcement learning, and emerging technologies., Key Deliverables
 * AI models and production-ready AI applications
 * Research prototypes and proof of concepts (POCs)
 * Model evaluation and benchmarking reports
 * AI solution architectures
 * Technical documentation
 * Experimentation reports
 * Reusable AI components and frameworks
 * Business impact assessments

Success Metrics

 * Model accuracy, precision, recall, and other performance metrics
 * Successful deployment of AI solutions into production
 * Business impact and measurable value delivered
 * Scalability, reliability, and efficiency of AI systems
 * Innovation through research contributions and new AI capabilities
 * Reduction in model inference latency and operational costs
 * Stakeholder satisfaction and adoption of AI solutions
 * On-time delivery of AI research and development milestones

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