Data and ML Engineer

Position Title: Data Engineer / Machine Learning Engineer with GenAI Expertise

Overview

We are seeking a highly skilled and motivated Data Engineer / Machine Learning Engineer to join our team. The ideal candidate will have expertise in Python, Apache Spark, Snowflake, Machine Learning (ML), and Generative AI (GenAI) technologies. This role involves designing and implementing data solutions, developing machine learning models, and leveraging generative AI to solve complex business problems.

Key Responsibilities

Data Engineering and Development

Design, build, and maintain scalable data pipelines using Apache Spark and Snowflake.

Develop ETL workflows to ingest, transform, and load structured and unstructured data into Snowflake.

Optimize queries and processes to enhance performance and minimize latency.

Machine Learning Model Development

Develop, train, and deploy machine learning models for predictive analytics and decision support.

Utilize Python libraries like Scikit-learn, TensorFlow, PyTorch, and Hugging Face for model building and evaluation.

Implement advanced techniques in natural language processing (NLP), computer vision, and deep learning.

Generative AI Implementation

Apply Generative AI (GenAI) models, such as GPT, DALL-E, or similar frameworks, to business use cases.

Fine-tune GenAI models to address specific requirements in text, image, or content generation tasks.

Research and implement innovations in generative AI to maintain competitive advantages.

Collaboration and Communication

Work with cross-functional teams to understand data needs and ensure delivery of scalable solutions.

Communicate findings, model outcomes, and business insights to both technical and non-technical stakeholders.

Required Skills and Qualifications

Educational Background: Bachelor s or Master s degree in Computer Science, Data Science, or a related field.

Programming Skills: Proficient in Python, including libraries like Pandas, NumPy, and PySpark.

Big Data Expertise: Hands-on experience with Apache Spark for large-scale data processing.

Cloud Data Warehousing: Proficiency with Snowflake or equivalent data warehouse platforms.

Machine Learning: Experience in developing and deploying ML models using Scikit-learn, TensorFlow, PyTorch, or similar tools.

Generative AI: Practical experience with GPT, DALL-E, Stable Diffusion, or other generative AI frameworks.

NLP and Deep Learning: Familiarity with Hugging Face transformers, BERT, and advanced neural network architectures.

Version Control: Experience with Git or other version control systems.

Preferred Skills

Experience in cloud platforms such as AWS, Azure, or Google Cloud (GCP).

Knowledge of CI/CD pipelines and MLOps best practices.

Familiarity with data visualization tools such as Tableau or Power BI.

Strong analytical, problem-solving, and communication skills.