Machine Learning Engineer

Reposted 14 Hours Ago Remote Hiring Remotely in US Senior level Remote Hiring Remotely in US Senior level Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders. The summary above was generated by AI

Paradigm Health is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. Our platform enhances trial efficiency and reduces the barriers to participation for healthcare providers. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm’s seamless infrastructure implemented at healthcare provider organizations, will bring potentially life-saving therapies to patients faster.

Our team hails from a broad range of disciplines and is committed to the company’s mission to create equitable access to clinical trials for any patient, anywhere. Join us, and bring your expertise, passion, creativity, and drive as we work together to realize this mission., As a Senior Machine Learning Engineer, you will take a leading role in designing and deploying sophisticated ML models, including GenAI and LLM-based solutions, that optimize clinical trial workflows and patient engagement. This position offers an opportunity to impact healthcare by developing state-of-the-art models that enhance trial design, accelerate patient recruitment, and improve overall trial efficiency. You will contribute to both high-level architecture decisions and hands-on implementation, driving the technology forward and influencing ML strategies across Paradigm., * Model Development & Deployment: Lead the development, testing, and deployment of ML models and pipelines, with a focus on scalability and integration into production systems.

• Advanced GenAI/LLM Applications: Design and refine GenAI/LLM-based models to streamline and automate clinical trial operations, from data gathering to real-time performance monitoring.
• Cross-Functional Collaboration: Partner with clinicians, informaticists, data scientists, and engineers to build solutions aligned with Paradigm’s mission and goals.
• Infrastructure & Performance Optimization: Drive improvements in model deployment infrastructure, develop monitoring tools, and refine model performance to ensure robust production-level reliability.
• Technical Leadership & Mentorship: Mentor junior ML engineers, contributing to team knowledge-sharing and establishing best practices for data science and machine learning.
• Strategic Communication: Present complex technical insights and results to both technical and non-technical stakeholders, advocating for data science-driven strategies that align with business objectives., Lead and grow an ML engineering team responsible for the end-to-end ML lifecycle: data collection, preprocessing, model development, deployment, evaluation and monitoring. Research and implement scalable ML and generative AI techniques (recommendation and agentic systems), mentor and hire engineers, drive pragmatic, business-focused solutions, and communicate technical results to stakeholders. Top Skills: Agentic SystemsGenerative AiMachine LearningMl InfrastructureRecommendation Systems Agero

• Education: Master’s or PhD in computer science, statistics, machine learning, or a related field.
• Experience: 5+ years of experience as a machine learning engineer, with a proven track record in healthcare, life sciences, or a related field.
• Technical Skills: Deep expertise in training, fine-tuning, and deploying ML models, including experience with GenAI/LLMs. Proficiency in Python, SQL, and familiarity with cloud infrastructure and ML engineering best practices.
• Production-Level ML Expertise: Experience managing production-level pipelines, including model deployment, monitoring, and continuous integration.
• Problem Solving & Collaboration: Advanced analytical skills and a collaborative approach to solving complex challenges across teams.
• Startup Mindset: Adaptability and experience in fast-paced, mission-driven environments with high levels of ambiguity.

Preferred:

• Healthcare/Clinical Trials Experience: Background in working with oncology or clinical trial data.
• GenAI/LLM Proficiency: Hands-on experience developing and deploying GenAI/LLM-based models and open-source frameworks for LLM applications.
• Startup Experience: Previous involvement in an early-stage startup, ideally in health tech or life sciences, with a passion for high-growth projects.

134K-181K Annually Senior level 134K-181K Annually Senior level Automotive * Big Data * Insurance * Software * Transportation Design, develop, and deploy machine learning models and pipelines to optimize operations. Lead full ML project lifecycle, ensure model evaluation/monitoring, collaborate cross-functionally, mentor junior engineers, and drive continuous improvement in ML applications and processes. Top Skills: AirflowAws EcrAws S3Aws SagemakerCi/CdDvcNumpyPandasPythonRestful ApisScikit-LearnSQL Block, 195K-343K Annually Senior level 195K-343K Annually Senior level Blockchain * eCommerce * Fintech * Payments * Software * Financial Services * Cryptocurrency Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI. Top Skills: AgentsAi InfrastructureEvaluation SystemsLlmsRetrieval Architectures

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