Senior Applied AI Engineer, Life Science Markets

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and deploy applications, services, and data workflows powered by AI.

• Collaborate closely with engineers, data scientists, and domain specialists.

• Oversee the implementation process from prototype to full production.

• Create and implement systems that integrate ML models, LLMs, retrieval, and workflow automation to address life sciences market inquiries.

• Make informed decisions regarding model quality, reliability, latency, and cost-effectiveness.

• Develop automated tests, evaluation datasets, and monitoring systems to ensure AI output and application reliability.

• Ensure thorough validation of predictive models, which includes point-in-time backtesting, baseline comparisons, and checks for leakage and coverage bias.

• Transition prototypes to production, managing APIs, integrations, deployment, observability, and incident resolution.

• Create reusable capabilities that can scale across various therapies, organizations, and clients.

• Engage directly with clients and domain experts to comprehend analytical workflows, articulate findings, challenge assumptions, and translate feedback into product priorities.

⛳️ Requirements

• Proven experience in independently delivering applied AI applications or services, from initial prototype stages to production deployment.

• Hands-on experience in integrating ML models and LLMs into software, encompassing retrieval, tool utilization, structured outputs, and evaluation.

• Sound judgment regarding model limitations and the ability to identify when a simpler approach is adequate.

• Capability to facilitate working sessions with both technical and non-technical stakeholders of clients to identify impactful solutions.

• Strong foundations in software engineering, including API design, testing, version control, and writing maintainable code.

• Experience in deploying and managing AI systems, including CI/CD processes, model versioning, monitoring, and troubleshooting.

• Proficient in handling large datasets in the cloud, preferably using AWS services like S3, Glue, EMR, MWAA, and SageMaker.

• Good judgment when dealing with incomplete or noisy data.

• Excellent communication skills and the ability to work autonomously within a cross-functional team and with client stakeholders.

• A background in life sciences, pharmaceutical analytics, or capital markets is advantageous but not mandatory.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Collaborative and innovative work environment.