Senior Ai Engineer

Description:

Enigma is seeking multiple Senior AI Engineers to join its remote US-based team to help advance innovative solutions at the intersection of AI, LLMs, and healthcare or clinical applications. This role is tailored for professionals who bring extensive experience in AI/ML development and who are passionate about building end-to-end solutions that empower data-driven decision-making.

You will lead and implement advanced machine learning models, pipelines, and LLM-driven architectures, contributing significantly to both strategic direction and hands-on engineering work. You’ll work closely with cross-functional teams across engineering, product, and business units.

Key Responsibilities:

• Lead the organization’s AI strategy by designing integrated solutions involving software engineering, statistical modeling, and machine learning for complex domains.

• Design and execute rigorous AI experiments to optimize product functionality and performance.

• Prepare and deliver analytical reports and data insights that guide business decisions.

• Serve as the subject matter expert on data assets, facilitating data collection, transformation, exploration, and accessibility.

• Promote seamless collaboration across software developers, engineers, and product analysts to drive scalable results.

Required Qualifications:

• 5–7 years of total experience, with 3+ years specifically as an AI Engineer.

• Advanced degree (MSc or Ph.D.) in Computer Science, AI, Machine Learning, or related field—or equivalent experience.

• Strong grasp of machine learning and statistical frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost.

• Excellent programming skills in Python, with experience in R, SQL, or similar languages.

• Deep understanding of deep learning, regression, classification, clustering algorithms, and model deployment practices.

• Hands-on experience working with LLMs, RAG (Retrieval-Augmented Generation) pipelines, and prompt engineering.

• Familiarity with tools like LangChain, LlamaIndex, Haystack, vector databases, Azure AI Studio, etc.

• Experience with MLOps, cloud infrastructure, orchestration tools, and observability platforms.

Bonus Experience:

• Experience in healthcare or clinical AI applications.

• Leadership or mentoring experience.