Artificial Intelligence Engineer

About the role

As an AI Engineer, you will play a critical role in building and scaling AI-powered capabilities that directly influence Epsilon’s products, platforms, and client outcomes. You will work alongside product managers, platform engineers, and data teams to translate complex business problems into production-ready AI systems. This role offers the opportunity to work on high-impact initiatives including generative AI, agentic workflows, and intelligent automation, while contributing to Epsilon’s broader goals of innovation, operational excellence, and data-driven decision making.

Responsibilities

• Design, develop, and deploy machine learning and AI models that are reliable, scalable, and production-ready
• Contribute to the development of generative AI and LLM-based solutions using techniques such as prompt engineering, retrieval-augmented generation (RAG), and fine-tuning
• Build and operate AI systems end-to-end, from experimentation and evaluation through deployment, monitoring, and iteration
• Collaborate with cross-functional partners to embed AI capabilities into customer-facing products and internal platforms
• Improve model performance, cost efficiency, and reliability through experimentation, tuning, and observability
• Help establish and evolve best practices for AI engineering, MLOps, and responsible AI within the organization
• Grow technically through exposure to modern AI frameworks, cloud-based ML platforms, and real-world enterprise use cases

Requirements

• 4+ years of experience building machine learning or AI-driven systems in real-world production environments
• Strong foundations in machine learning, statistics, data structures, and software engineering
• Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• Proficiency in Python and experience applying production-grade engineering practices
• Familiarity with cloud environments (AWS, Azure, or GCP) and deploying services at scale
• Ability to work across the full AI lifecycle—from data exploration and modeling to deployment and monitoring
• Strong problem-solving skills and comfort operating in ambiguous or evolving problem spaces

Qualifications

Experience that may set you apart:

• Experience working with large language models (LLMs), generative AI systems, or agent-based architectures
• Exposure to RAG pipelines, evaluation frameworks, or fine-tuning foundation models
• Familiarity with MLOps tooling, CI/CD pipelines, model monitoring, or feature stores
• Experience collaborating closely with product and platform teams on customer-facing AI features
• MS degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent practical experience)

Pay

Base Salary: $73,500.00 - $136,500.00. Actual compensation within the range will be dependent upon, but not limited to the individual’s skills, experience, qualifications, location, and applicable employment laws.

Benefits

• Time to Recharge: Flexible time off (FTO), 15 paid holidays
• Time to Recover: Paid sick time
• Family Well-Being: Parental/new child leave, childcare & elder care assistance, adoption assistance
• Extra Perks: Comprehensive health coverage, 401(k), tuition assistance, commuter benefits, professional development, employee recognition, charitable donation matching, health coaching and counseling

Epsilon benefits are subject to eligibility requirements and other terms.