Data Scientists

Job Description Summary

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.

Job Description

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