Architect ML - AI Researcher

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Architect ML - AI Researcher based in the United States.

This role sits at the intersection of advanced machine learning research, applied AI architecture, and large-scale production engineering, with a strong focus on healthcare innovation. You will design and deploy next-generation AI systems powered by LLMs and GenAI, translating complex research into scalable, production-ready solutions that directly improve clinical and business outcomes. The environment is highly collaborative and global, involving cross-functional teams across data science, engineering, and product. You will work on cutting-edge use cases such as predictive healthcare modeling, semantic search, and AI-driven clinical insights. The position blends deep technical research with hands-on architecture leadership in cloud-native environments. It is ideal for someone who thrives in solving complex real-world problems with measurable impact.

• Lead the design and architecture of scalable ML/AI systems, integrating GenAI and LLM-based solutions into cloud-native SaaS platforms, particularly in healthcare contexts.
• Develop, evaluate, and optimize machine learning models for use cases such as prediction, summarization, classification, semantic search, and clinical decision support.
• Conduct applied research, experimentation, and model evaluation using modern frameworks and responsible AI practices, including fairness, safety, and performance validation.
• Build and oversee data pipelines and ML workflows leveraging large-scale datasets and big data technologies such as Spark, Databricks, or cloud data lakes.
• Collaborate with global engineering, data science, and clinical teams to translate business and healthcare requirements into robust technical solutions.
• Lead architectural discussions with clients and stakeholders, providing technical direction, troubleshooting guidance, and strategic recommendations.
• Mentor engineering teams and contribute to best practices in ML system design, deployment, and lifecycle management.

Requirements:

• 10+ years of experience in machine learning, data science, or AI engineering, with at least 1+ year in healthcare-focused ML/AI environments.
• Advanced degree (PhD with 1+ year experience or Master’s with 4+ years of experience) in Computer Science, AI, Data Science, or related fields.
• Strong hands-on expertise in Python, SQL, and ML frameworks such as PyTorch, Scikit-learn, Pandas, NumPy, and LightGBM.
• Proven experience deploying ML systems in production SaaS environments using cloud platforms such as AWS, Azure, or Google Cloud.
• Deep understanding of transformer architectures, LLMs, and techniques such as RAG, PEFT (LoRA/QLoRA), prompt tuning, and agentic frameworks (e.g., LangChain, LlamaIndex).
• Experience working with healthcare data formats such as EHR, ADT, and clinical notes is strongly preferred.
• Strong background in distributed systems, CI/CD pipelines, MLOps, and scalable AI system design.
• Excellent communication and leadership skills, with experience mentoring teams and leading complex, multi-stakeholder projects.
• Ability to bridge research and business impact, translating technical outputs into actionable insights and measurable outcomes.

Benefits:

• Remote-first opportunity within the United States.
• Work on cutting-edge AI, ML, GenAI, and cloud-native solutions with real-world healthcare impact.
• Exposure to enterprise-scale projects with leading global clients across multiple industries.
• Opportunity to work in a research-driven, innovation-focused environment with strong emphasis on applied AI.
• Continuous learning and upskilling opportunities in advanced AI frameworks and emerging technologies.
• Collaborative, global team culture with strong mentorship and leadership development opportunities.
• Engagement with award-winning AI initiatives and high-impact production systems at scale.