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.

Accountabilities

• 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.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

Data Privacy Notice

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws. You may exercise your rights at any time.

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