Applied AI Scientist

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

https://job.goodword.io/JobLanding/JobId=8f309243-7828-4877-8d84-d51dd5cf89ab?trafficsourceid=0 external

• 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