Data Engineer (AI/ML) Contract

Role Overview

The AI/ML Specialist will play a pivotal role in designing and implementing advanced AI solutions that address complex business challenges. Collaborating with cross-functional teams, this role will leverage expertise in machine learning, deep learning, and emerging AI technologies to enhance product offerings, optimize operations, and drive innovation across customer experiences.

Key Responsibilities

• Apply AI/ML expertise to build scalable solutions in areas such as Generative AI, personalization, image and speech recognition, NLP, recommendation systems, and time series forecasting.
• Lead the full solution lifecycle: problem identification, data collection, analysis, modeling, validation, and deployment of production-grade systems.
• Research and experiment with emerging academic ideas to solve new business problems and improve existing solutions.
• Define and implement deployment strategies for AI solutions in cloud infrastructure at scale.
• Drive technical design reviews, ensuring high-quality, maintainable code and integration with CI/CD pipelines.
• Provide mentorship to junior team members and foster technical excellence across the team.
• Actively contribute to business and technical forums, influencing strategy and innovation.

Qualifications

• Advanced degree in Computer Science, Engineering, Statistics, Mathematics, or related quantitative discipline
• Proven track record of impactful research, with publications or patents a plus.
• Extensive experience building and deploying sophisticated AI/ML solutions at scale.
• Expertise in one or more fields: Generative AI, Deep Learning, NLP, Reinforcement Learning, Recommendation Systems, Bayesian Inference, or advanced time series forecasting.
• Hands-on experience with open-source tools and frameworks, including Airflow, Kubeflow, Docker, Kubernetes, MLflow, TensorFlow, PyTorch, Scikit-learn, and feature stores.
• Good programming skills in Python, Java, Scala, or Julia, with proficiency in modern IDEs and ML libraries.
• Solid understanding of agile methodologies, with experience leading projects in dynamic environments.
• Excellent communication and leadership skills, with the ability to collaborate across technical and non-technical teams.
• Experience with cloud platforms (GCP, AWS) is a plus.