Position Summary
We are seeking an experienced Data Scientist with strong AI/ML expertise to design, develop, and deploy advanced machine learning solutions that drive business value. The ideal candidate will possess hands-on experience in predictive modeling, deep learning, Generative AI, large language models (LLMs), and data engineering practices, along with strong programming and analytical skills.
Key Responsibilities
- Design, develop, and deploy scalable Machine Learning and AI solutions.
- Build predictive models, classification models, recommendation systems, forecasting models, and anomaly detection solutions.
- Develop and fine-tune Generative AI applications using LLMs such as GPT, Llama, Claude, or similar models.
- Implement NLP solutions including sentiment analysis, text classification, summarization, and document intelligence.
- Perform data cleansing, feature engineering, exploratory data analysis (EDA), and model evaluation.
- Develop and optimize deep learning models using TensorFlow, PyTorch, or Keras.
- Create data pipelines for model training, inference, and monitoring.
- Collaborate with business stakeholders to translate business requirements into AI-driven solutions.
- Deploy AI/ML solutions on cloud platforms including AWS, Azure, or Google Cloud Platform.
- Monitor model performance and implement model retraining strategies.
- Stay updated with advancements in AI, Machine Learning, Generative AI, and MLOps technologies.
Required Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.
- 12+ years of experience in Data Science and Machine Learning.
- Strong programming skills in Python.
- Experience with Machine Learning libraries such as:
- Scikit-Learn
- TensorFlow
- PyTorch
- Keras
- XGBoost
- Experience with SQL and large-scale data processing.
- Strong understanding of supervised and unsupervised learning algorithms.
- Hands-on experience with:
- Classification
- Regression
- Clustering
- Time Series Forecasting
- Recommendation Systems
- Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
- Proficiency in data visualization tools such as Power BI, Tableau, or Matplotlib.
- Experience with Git and CI/CD pipelines.
Preferred Qualifications
- Experience with Generative AI, LLMs, LangChain, LlamaIndex, RAG, Vector Databases (Pinecone, Weaviate, ChromaDB).
- Knowledge of MLOps tools such as MLflow, Kubeflow, Airflow, or SageMaker.
- Experience with Spark, Databricks, and Big Data ecosystems.
- Familiarity with Docker, Kubernetes, and containerized deployments.
- Azure AI Services, Azure ML Studio, OpenAI, or AWS Bedrock experience.
- Experience building production-grade AI applications.
Technical Skills
Programming: Python, SQL, R
AI/ML: Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI, LLMs
Frameworks: Scikit-Learn, TensorFlow, PyTorch, Keras, Hugging Face
Cloud: AWS, Azure, Google Cloud Platform
MLOps: MLflow, Kubeflow, Airflow, Docker, Kubernetes
Big Data: Spark, Databricks, Hadoop
Visualization: Tableau, Power BI, Matplotlib, Seaborn
Nice-to-Have
- Experience with Chatbots and AI Assistants.
- Retrieval-Augmented Generation (RAG) implementation experience.
- Prompt Engineering expertise.
- Experience with OpenAI, Anthropic Claude, Gemini, or Llama models.
Keywords
Data Scientist, AI Engineer, Machine Learning Engineer, Generative AI, LLM, NLP, Deep Learning, Python, TensorFlow, PyTorch, OpenAI, Azure AI, AWS SageMaker, Databricks, MLOps, RAG, LangChain.