AI Research Scientist

Job Description

We are seeking an innovative and highly motivated AI Research Scientist to join our Artificial Intelligence Research team. In this role, you will conduct cutting-edge research in Machine Learning (ML), Deep Learning, Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning to develop next-generation AI solutions. You will work closely with AI Engineers, Machine Learning Engineers, Data Scientists, and Product teams to transform research ideas into scalable, production-ready AI systems.

The ideal candidate has a strong background in AI research, advanced mathematics, statistical modeling, and software development. You should be passionate about solving complex problems, publishing high-impact research, and advancing the state of artificial intelligence.

Key Responsibilities

• Conduct research in machine learning, deep learning, and Generative AI.
• Design and develop novel AI algorithms and architectures.
• Train, fine-tune, and evaluate large language models (LLMs) and foundation models.
• Build AI prototypes and proof-of-concept applications.
• Research Retrieval-Augmented Generation (RAG), AI agents, and multimodal AI systems.
• Design experiments and analyze research results using statistical methods.
• Publish technical papers, patents, and research findings when appropriate.
• Collaborate with AI Engineers to deploy research into production environments.
• Optimize AI model accuracy, scalability, efficiency, and inference performance.
• Develop and improve NLP, computer vision, and speech recognition models.
• Work with large structured and unstructured datasets for model training.
• Evaluate emerging AI technologies, open-source frameworks, and research publications.
• Implement responsible AI, fairness, explainability, and model governance practices.
• Mentor junior researchers and contribute to technical knowledge sharing.
• Present research outcomes and technical recommendations to engineering teams and leadership.

Required Qualifications

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, or a related field.
• 3–7+ years of experience in AI research, machine learning, or applied AI development.
• Strong programming skills in Python.
• Deep understanding of machine learning, deep learning, probability, optimization, and statistics.
• Experience building and evaluating large-scale AI models.
• Strong analytical, problem-solving, and research skills.
• Excellent written and verbal communication skills.
• Ability to work in cross-functional, research-driven environments.

Preferred Qualifications

• Experience with Generative AI, LLMs, RAG systems, AI agents, or multimodal AI.
• Publications in peer-reviewed AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, CVPR).
• Experience with distributed training and GPU-based computing.
• Knowledge of AI safety, explainability, and responsible AI principles.
• Experience with cloud-based AI platforms (AWS, Azure, or Google Cloud).
• Familiarity with MLOps, model deployment, and production AI systems.

Technical Skills

• Artificial Intelligence
• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Statistics & Probability
• Data Modeling
• Feature Engineering
• Model Optimization
• Prompt Engineering
• AI Evaluation
• Responsible AI
• AI Governance
• Distributed Computing
• Research Methodology

Preferred Tools & Technologies

• Python
• PyTorch
• TensorFlow
• JAX
• Scikit-learn
• Hugging Face Transformers
• LangChain
• LlamaIndex
• OpenAI API
• Anthropic Claude API
• Google Gemini API
• MLflow
• Kubeflow
• Docker
• Kubernetes
• Apache Spark
• Airflow
• Weaviate
• Pinecone
• FAISS
• ChromaDB
• Git
• GitHub
• Linux
• CUDA
• NVIDIA GPUs
• AWS SageMaker
• Microsoft Azure AI
• Google Vertex AI

Benefits

• Competitive salary with annual performance bonus
• Equity or Restricted Stock Units (RSUs), where applicable
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Flexible remote and hybrid work options
• Professional development and conference sponsorship
• Tuition and certification reimbursement
• Employee wellness and mental health programs
• Career growth opportunities in AI research and innovation