Senior Machine Learning/ Backend Engineer

About the role
We are hiring an exceptional Senior Machine Learning Backend Engineer to lead the integration of advanced ML solutions into our platform. At Plenful, we believe the Engineering-Product-Design (EPD) triangle is essential to our product’s success. As a Senior ML Backend Engineer, you will own the end-to-end development of ML-driven features—designing scalable systems, deploying models into production, and ensuring performance, compliance, and reliability in healthcare workflows.

• Design, build, and maintain backend services and APIs in Python, with a focus on integrating and deploying machine learning models.
• Architect scalable infrastructure on AWS (S3, Lambda, SQS, ECS, CloudWatch) to support ML pipelines and inference at scale.
• Collaborate with product managers, designers, data scientists, and engineers to define and deliver ML-powered product features.
• Deploy, monitor, and optimize ML models in production, ensuring performance, security, and compliance with HIPAA and other healthcare regulations.
• Develop and optimize data pipelines for training, inference, and real-time decision-making.
• Implement best practices for CI/CD, testing (Pytest), and version control (Git) to ensure reliable ML feature deployment.
• Troubleshoot and resolve production issues across ML services, APIs, and infrastructure.
• Document architectural decisions, ML workflows, and compliance/security practices.
• Provide technical leadership—mentoring engineers, reviewing code, and championing backend + ML integration best practices.

What we’re looking for

• 3+ years of professional backend development experience, with a Bachelor’s degree in Computer Science, Machine Learning, or a related field.
• Expertise in Python for backend services and ML integration.
• Strong applied ML experience in a SaaS context—NLP pipelines, LLM fine-tuning/evaluation, or healthcare ML applications.
• Familiarity with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or Hugging Face Transformers.
• Hands-on experience with cloud infrastructure (AWS: S3, Lambda, ECS, SQS, CloudWatch).
• Proficiency in relational databases (PostgreSQL) and designing schemas to support ML applications.
• Experience deploying ML models into production systems, not just research or prototyping.
• Solid understanding of CI/CD pipelines, Git workflows, and automated testing for ML/Backend systems.
• Proven track record of owning projects end-to-end in a fast-paced startup or B2B SaaS environment.
• Experience in regulated industries (healthcare, HIPAA compliance) preferred.
• Strong communication skills with the ability to translate ML concepts into product outcomes.

Plenful perks

• Great benefits include unlimited PTO, health insurance, meal stipend, health & wellness stipend, team offsites, 401K matching, and stock options
• Opportunities to further develop and refine your partnership acumen by partnering with our seasoned leaders