Senior AI/ML Engineer

What is the project, and why should you care?

As an AI/ML Engineer, you will be part of unique Data and AI service lines, with a specific focus on delivering data engineering and AI solutions across various projects. Furthermore, you will be responsible for designing and implementing Python-based data-processing services and data pipelines while being part of a team of highly skilled professionals focused on AI and ML projects. You can work in various fields, such as Natural Language Processing (NLP), Large Language Models (LLMs), Recommendation Systems, conversational AI, chatbots, vector databases, and other API-based process automation projects. Leveraging your Python data engineer expertise, you can develop ETL pipelines and other data manipulation services and contribute to Data and AI architectures.

You will be an excellent fit for this position if you have:

• Bachelor’s degree in Computer Science, Information Technology, or a related field
• Proven experience as an AI/ML, Data Engineer, or a similar role
• Strong proficiency in Python and experience with relevant frameworks and libraries, such as pandas, pyspark, numpy, sklearn, matplotlib, etc.
• Familiarity with SQL
• Knowledge of some cloud platforms (e.g., AWS, Azure, GCP) and their services
• Familiarity with AI/ML technologies (e.g., Computer Vision, NLP, anomaly detection)
• Understanding AI tools and concepts like LLMs, ChatGPT, RAG, etc.
• Excellent problem-solving and communication skills
• Ability to work independently and collaboratively in a fast-paced environment
• Experience with ETL processes and tools is preferred (e.g., Airflow, AWS Glue)

Here are some of the things you’ll be working on:

• Develop highly scalable services realizing AI/ML functionalities (e.g., NLP, M,L and AI models)
• Implement various machine learning solutions addressing computer vision and NLP use cases
• Work with Large Language Models (LLMs) and perform prompt engineering tasks
• Design and implement data transformation services for various use cases, such as automatic translation and transcription, Text2SQL, and intent and gesture recognition
• Data Pipeline Development: Design, build, and maintain robust and scalable data pipelines for extracting, transforming, and loading (ETL) data from various sources
• Use AWS cloud to implement AI/ML solutions (e.g., Bedrock, Sagemaker, Lambda, Textract)