Artificial Intelligence Engineer

Company Description Kepler 22 LLC delivers specialized IT staffing and recruiting solutions that help organizations address complex technology talent needs. The company provides contract staffing, direct placement, and staff augmentation across application development, infrastructure services, and business process outsourcing. With strong technology expertise and a structured recruiting methodology, Kepler 22 aligns high-quality technical talent with business objectives and delivery timelines. IT professionals gain access to diverse consulting and permanent roles, along with personalized career guidance and positioning support. Guided by transparency and accountability, Kepler 22 focuses on building long-term partnerships that power innovation and sustainable business growth.

Role Description The Artificial Intelligence Engineer will design, develop, and deploy AI models and systems that solve real-world business problems for Kepler 22 LLC clients. In this full-time, on-site role based in New York, NY, the engineer will work closely with cross-functional teams to understand requirements, define solution architectures, and implement AI-based features and services. Day-to-day responsibilities include building and training machine learning and deep learning models, performing data preprocessing and feature engineering, and integrating AI components into production software environments. The engineer will evaluate model performance, conduct experiments, refine algorithms, and document technical designs and implementation details. The role also involves collaborating with stakeholders to translate complex technical concepts into clear recommendations and participating in code reviews, best-practice sharing, and continuous improvement initiatives.

Qualifications

• Strong foundation in Computer Science and Software Development, including data structures, algorithms, object-oriented programming, and version control,(0-3) years.
• Hands-on experience with Neural Networks and Pattern Recognition, including model design, training, evaluation, and optimization.
• Practical expertise in Natural Language Processing (NLP), such as text classification, sequence modeling, and language understanding.
• Proficiency with common AI/ML tools and frameworks (e.g., Python, TensorFlow, PyTorch, scikit-learn) and experience working with large datasets.
• Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent practical experience).
• Ability to collaborate in cross-functional teams, communicate complex ideas clearly, and manage priorities in a fast-paced environment.
• Experience deploying models to production (APIs, microservices, or cloud platforms such as AWS, GCP, or Azure) is highly beneficial.
• Familiarity with MLOps practices, data pipelines, and monitoring of AI systems in production is a plus.