Lead ML Engineer

Job summary

Practice - AIA - Artificial Intelligence and Analytics About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need.

Benefits

Qualifications

• By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need.
• Design and develop predictive, generative AI, and recommendation models to improve operational efficiency, customer experience, and business outcomes.
• What you need to have to be considered
• 8+ years of experience in Machine Learning, Data Science, Artificial Intelligence, or Advanced Analytics roles, with experience leading enterprise AI initiatives.
• Strong expertise in Python and machine learning libraries including Pandas, Scikit-learn, XGBoost, LightGBM, and PyTorch.
• Hands-on experience developing and deploying machine learning models in Azure Machine Learning environments.
• Experience designing and implementing Generative AI and Azure OpenAI solutions for enterprise use cases.
• Strong proficiency in SQL and experience working with Snowflake for analytics and machine learning workloads.
• Experience with model development lifecycle management, MLOps practices, model monitoring, and deployment automation.
• Proficiency with GitHub, Docker, CI/CD pipelines, and modern software engineering practices.
• Strong understanding of machine learning algorithms, feature engineering, model evaluation, recommendation systems, and predictive analytics.
• Experience working with large-scale structured and unstructured datasets in cloud-based environments.

Responsibilities

• In this role, you will:

Skills

Degrees

Industry

Company size