About the Role
This role involves leveraging advanced machine learning models and AI-driven solutions to address complex business problems.
Responsibilities
- AI/ML Model Development: Design and train machine learning models using various algorithms, including deep learning, NLP, and computer vision.
- Databricks Orchestration: Build and optimize end-to-end AI/ML pipelines on Databricks, utilizing Unity Catalog for governance and MLflow for experiment tracking.
- Generative AI & LLMs: Implement advanced AI patterns such as Retrieval-Augmented Generation (RAG) and fine-tune pre-trained models for specific enterprise tasks.
- Python Expertise: Write production-quality, idiomatic PySpark and Python code that leverages Spark’s distributed nature.
- Collaboration: Partner with Engineering and Product teams to translate business problems into scalable analytical solutions.
- Insight Extraction: Perform exploratory data analysis (EDA) and extract meaningful insights from massive, complex datasets to drive strategic decisions.
Qualifications
- Education: MS or PhD in a quantitative field such as Computer Science, Statistics, or Math.
- Experience: 5+ years of hands-on experience in data science or AI engineering in high-growth environments.
Required Skills
- Technical Proficiency: Expert-level Python (pandas, NumPy, scikit-learn, PySpark).
- Extensive experience with Apache Spark for large-scale data processing.
- Proficiency in SQL for data manipulation and querying in Lakehouse environments.
- AI Foundations: Strong understanding of statistics, probability, and advanced ML lifecycle management (MLOps).
Preferred Skills
- Experience with Deep Learning frameworks (TensorFlow, PyTorch).
- Familiarity with Cloud Platforms (AWS, Azure, or Google Cloud Platform) and their native data services.
- Databricks certifications, such as Databricks Certified Machine Learning Professional.
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
AI & Machine Learning
Seniority Level:
Senior