Data Scientist

Data Scientist with deep expertise in modern AI/ML technologies to join our innovative team. This role combines cutting-edge research in machine learning, deep learning, and generative AI with practical full-stack cloud development skills. You will be responsible for architecting and implementing end-to-end AI solutions, from data engineering pipelines to production-ready applications leveraging the latest in agentic AI and large language models.

Key Responsibilities

AI/ML Development & Research

• Design, develop, and deploy advanced machine learning and deep learning models for complex business problems
• Implement and optimize Large Language Models (LLMs) and Generative AI solutions
• Build agentic AI systems with autonomous decision-making capabilities
• Conduct research on emerging AI technologies and their practical applications
• Perform model evaluation, validation, and continuous improvement

Cloud Infrastructure & Full-Stack Development

• Architect and implement scalable cloud-native ML/AI solutions on AWS, Azure, or GCP
• Develop full-stack applications integrating AI models with modern web technologies
• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)
• Implement CI/CD pipelines for ML model deployment and monitoring
• Design and optimize cloud infrastructure for high-performance computing workloads

Data Engineering & Database Management

• Design and implement data pipelines for large-scale data processing
• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)
• Optimize database performance for ML workloads and real-time applications
• Implement data governance and quality assurance frameworks
• Handle streaming data processing and real-time analytics

Leadership & Collaboration

• Mentor junior data scientists and guide technical decision-making
• Collaborate with cross-functional teams including product, engineering, and business stakeholders
• Present findings and recommendations to technical and non-technical audiences
• Lead proof-of-concept projects and innovation initiatives

Required Qualifications

Education & Experience

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or related field
• 5+ years of hands-on experience in data science and machine learning
• 3+ years of experience with deep learning frameworks and neural networks
• 2+ years of experience with cloud platforms and full-stack development

Technical Skills - Core AI/ML

• Machine Learning: Scikit-learn, XGBoost, LightGBM, advanced ML algorithms
• Deep Learning: TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, Transformers
• Large Language Models: GPT, BERT, T5, fine-tuning, prompt engineering
• Generative AI: Stable Diffusion, DALL-E, text-to-image, text generation
• Agentic AI: Multi-agent systems, reinforcement learning, autonomous agents

Technical Skills - Development & Infrastructure

• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript
• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI
• Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra, DynamoDB)
• Full-Stack Development: React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes
• MLOps: MLflow, Kubeflow, Model versioning, A/B testing frameworks
• Big Data: Spark, Hadoop, Kafka, streaming data processing

Preferred Qualifications

• Experience with vector databases and embeddings (Pinecone, Weaviate, Chroma)
• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks
• Experience with model compression and edge deployment
• Familiarity with distributed computing and parallel processing
• Experience with computer vision and NLP applications
• Knowledge of federated learning and privacy-preserving ML
• Experience with quantum machine learning
• Expertise in MLOps and production ML system design

Key Competencies

Technical Excellence

• Strong mathematical foundation in statistics, linear algebra, and optimization
• Ability to implement algorithms from research papers
• Experience with model interpretability and explainable AI
• Knowledge of ethical AI and bias detection/mitigation

Problem-Solving & Innovation

• Strong analytical and critical thinking skills
• Ability to translate business requirements into technical solutions
• Creative approach to solving complex, ambiguous problems
• Experience with rapid prototyping and experimentation

Communication & Leadership

• Excellent written and verbal communication skills
• Ability to explain complex technical concepts to diverse audiences
• Strong project management and organizational skills
• Experience mentoring and leading technical teams