What is this opportunity?

At Eleos, we build a behavioral health CareOps automation platform that transforms therapy conversations into structured insights and clinical documentation. Our system uses advanced ML and LLM technologies to improve care quality, support therapists’ daily workflows, and reduce documentation time by over 50%.

As a Senior ML Infrastructure Engineer, you will design and build the infrastructure that powers our ML and LLM systems in production. You will develop scalable pipelines, systems, and tools that enable data scientists and AI teams to efficiently develop, test, and deploy models.
Working closely with data scientists, engineers, and product teams, you will ensure our ML capabilities are reliable, scalable, and production-ready—helping bring cutting-edge AI to improve mental health care.
This is a unique opportunity to join a startup with a real impact on thousands of people’s wellbeing and mental health, applying cutting-edge AI technologies to solve meaningful human problems.

How will you contribute?

• Design and build infrastructure and backend services supporting ML and LLM systems
  
  
• Develop and maintain ML training and deployment pipelines
  
  
• Build tooling that enables model experimentation, versioning, and reproducibility
  
  
• Implement CI/CD pipelines for ML workflows and model deployment
  
  
• Support LLM deployment, prompt management, and optimization pipelines
  
  
• Improve reliability, monitoring, and observability of ML systems in production
  
  
• Collaborate with data scientists to productionize models and research prototypes
  
• Ensure secure and compliant handling of sensitive healthcare data
  
  

What qualifications and skills will help you be successful?

• 5+ years of industry experience in ML Infrastructure, Backend Engineering, or related fields
  
  
• Strong Python experience with production-grade systems
  
  
• Experience working with cloud platforms (AWS, GCP, or Azure)
  
  
• Experience with containerization technologies (Docker, Kubernetes)
  
  
• Experience building CI/CD pipelines for ML systems or backend services
  
  
• Experience supporting LLM deployment or ML models in production
  
  
• Familiarity with model versioning, experiment tracking, and ML tooling
  
  

Some nice to haves are:

• Experience with prompt engineering and prompt management
  
  
• Experience with data versioning tools (DVC, Pachyderm, etc.)
  
  
• Experience with MLOps platforms (MLflow, Kubeflow, etc.)
  
  

What is this opportunity?

We are looking for a Senior Backend Developer to join our engineering team. You will focus on developing and maintaining the server-side logic and infrastructure that power our innovative applications.

Who are you?

This is an opportunity to build foundational systems that directly impact how healthcare providers deliver care. Your work will power the platform that thousands of clinicians rely on daily, combining technical challenges with meaningful real-world impact.

How will you contribute?

• Audio Processing Pipeline - Design and scale our audio processing infrastructure to handle high volumes with low latency and maximum reliability
• LLM Integration & Production - Partner with Data Scientists to instrument, deploy, and operationalize Large Language Models in production environments
• Backend Platform - Lead platformization efforts to create abstractions, tooling, and frameworks that elevate backend development across the organization
• Modern Tech Stack - Build with Python, FastAPI, Kafka, and Airflow while helping shape our technical evolution
• Company-Wide Initiatives - Drive high-impact projects that define product capabilities and technical direction

What We're Looking For

• 5+ years of backend engineering experience
• Strong foundation in building and scaling distributed systems and data pipelines
• Experience with event-driven architectures and workflow orchestration (Kafka, Airflow, or similar)
• Modern API development experience (FastAPI, or equivalent frameworks)
• Interest in ML/AI infrastructure and bringing models to production
• Team player who thrives on collaboration and working cross-functionally
• Passion for infrastructure, platform thinking, and operational excellence
• Bonus: Experience with audio processing, LLM deployment, or healthcare technology

This is a unique opportunity to join a startup that has a meaningful impact on the well-being and mental health of thousands. 

We have:

• A product that positively impacts people's lives every single day.
• A team of amazing people with a shared vision and the infinite drive to make it happen
• We offer significant equity.
• Opportunity to build, grow, and become highly instrumental in shaping how technology can increase the effectiveness of therapy
• Hybrid work opportunities.
• On mental health days off, you can take any given moment simply because you need them.

• Design, implement, and maintain scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.
• Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all Eleos Health products.
• Monitor and improve uptime, reliability, and observability of our data infrastructure and pipelines.
• Build and maintain systems to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.
• Work closely with product and engineering teams to deliver new features rapidly and with a high standard of technical excellence.
• Drive innovation in how we build, measure, and optimize data features, backend services, and AI product integrations.
• Participate in on-call rotations with a service-oriented approach and fast responsiveness.
• Lead scalability efforts to support increasing data volumes, expanding AI/ML initiatives, and new product launches.

• At least 5 years of experience with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.
• Hands-on experience working on ML/AI-powered products in production, with strong understanding of requirements for integrating data platforms with AI features.
• Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, and experience supporting their deployment or integration.
• Familiar with or have worked with these technologies (or alternatives):
  • Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
  • API Development: FastAPI, micro-service architecture, SFTP
  • Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
  • ML/AI: ML/LLM libraries and frameworks (such as Gemini, Hugging Face, etc.)
  • Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
• Demonstrated ability to optimize performance and ensure high availability, scalability, and reliability of backend/data systems.
• Strong foundation in best practices for data quality, governance, security, and observability.
• Ability to collaborate effectively with engineering, data science, and product teams in a cross-functional setting.
• Track record of innovative thinking on feature-level implementations, metric definitions, and AI/data integrations.
• Service-oriented approach, particularly in high-responsibility, on-call situations.

This is a unique opportunity to join a startup that is having a meaningful impact on the well-being and mental health of thousands. We have

• A product that positively impacts peoples' lives every single day.
• A team of amazing people with a shared vision and the infinite drive to make it happen
• We offer significant equity.
• Opportunity to build, grow and become highly instrumental in shaping how technology can increase the effectiveness of therapy.
• Hybrid work opportunities. 
• Mental health days off you can take any given moment simply because you need them.