Senior Machine Learning Engineer
Careaccess · USA Remote
About this role
**Senior Machine Learning Engineer — Care Access** **About Care Access** Care Access is working to make the future of health better for all. With hundreds of research locations, mobile clinics, and clinicians across the globe, we bring world-class research and health services directly to communities that often face barriers to care. **How This Role Makes a Difference** As a **Senior Machine Learning Engineer**, you’ll build cutting-edge AI products that impact how new therapies reach patients. You’ll turn advanced ML/AI research into scalable, real-world solutions—while collaborating closely with cross-functional teams and continuously improving systems through automation. --- ## How You’ll Make an Impact - **Build and deploy AI-driven products** that accelerate clinical trials and improve patient outcomes. - **Develop advanced ML models and LLM-powered agents** for use cases such as patient recruitment, enrollment forecasting, and study feasibility (and help expand the AI knowledge base architecture). - **Leverage modern cloud tools and MLOps best practices** to build robust data pipelines and deploy models at scale (e.g., **Python/Clojure**, **AWS** services like Athena/Bedrock/SageMaker, **dbt**, **Prefect**, and **CI/CD** with monitoring). - **Collaborate across teams** (data scientists, product managers, designers, engineers, and domain experts) to integrate AI capabilities into the platform and support clinical research workflows. - **Continuously learn and innovate**, staying current with ML/AI (LLMs, NLP, probabilistic modeling, etc.) and moving promising prototypes into production. --- ## The Expertise Required - **Strong programming & data skills:** Proficiency in **Python** and ML ecosystem (pandas, scikit-learn, TensorFlow/PyTorch). Comfortable with large datasets, complex SQL, and modern data processing frameworks. **Functional programming (e.g., Clojure)** is a plus. - **Cloud & MLOps expertise:** Experience with **AWS (or similar)** and **Docker**. Familiar with CI/CD, automated testing, and monitoring (model performance and data drift). - **Deep ML/AI knowledge:** Strong fundamentals (model selection, training, evaluation, feature engineering) and statistical modeling. **NLP and LLMs** are important. - **Analytical problem-solving:** Ability to break down complex problems and deliver pragmatic, maintainable ML solutions that are accurate and performant in production. - **Mission-driven mindset:** Passion for speeding up clinical trials and improving patient outcomes; empathy for patients, clinicians, and researchers; commitment to unbiased AI. --- ## Certifications / Licenses, Education, and Experience - **Minimum Experience:** **5+ years** building and deploying machine learning solutions in production at scale, including end-to-end ML pipelines from data ingestion to model serving. --- ## How We Work Together - **Location:** **Remote within the United States** (100% remote). - **Travel:** **< 10%** travel; occasional planned travel may be required. - **Physical demands:** Ability to use keyboards and other computer equipment. **Pay Range (US):** **$140,000 – $190,000 USD/year** (full-time) --- ## Benefits & Perks (US Full Time Employees) - Paid Time Off (PTO) and Company Paid Holidays - 100% employer-paid medical, dental, and vision insurance options - Health Savings Account (HSA) and Flexible Spending Accounts - Bi-weekly HSA employer contribution - Company paid Short-Term Disability and Long-Term Disabil
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