Filtr uses AI to scan 1000+ jobs and finds postings that perfectly matches your resume

The company is looking to solve the problem of administrative complexity in the healthcare industry by building AI-driven software.

Requirements

• Strong experience running and evaluating ML models (e.g., LLMs, classification, recommendation, etc.).
• Proficient in building APIs and services to serve models in production environments.
• Experience building ML pipelines for training, evaluation, and testing using tools like Airflow, MLflow, Weights & Biases, or similar.
• Solid understanding of data modeling, data storage, and data engineering fundamentals for ML use cases.
• Comfortable with versioning, benchmarking, and monitoring models in production.
• Experience with modern languages (e.g., Python, TypeScript, Go) and scalable infra (e.g., Docker, Kubernetes, serverless).

Responsibilities

• Run hands-on experiments with third-party and in-house AI models to test performance, quality, and viability for real-world use cases.
• Design and implement robust, production-ready AI services that integrate ML models into user-facing applications.
• Develop and maintain pipelines for model evaluation, offline testing, and continuous integration of model updates.
• Design scalable data models and storage strategies for ML data, including features, labels, metadata, and evaluation metrics.
• Write clean, testable code in modern languages and deploy via scalable infra.

Other

• Collaborate with research, product, and infrastructure teams to align model performance with business objectives and production constraints.
• 3+ years of software engineering experience, including 2+ years in ML-focused roles.