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Our client, an exciting HealthTech company, are hiring a Senior Full Stack Engineer to join the team in New York. The successful candidate will play a key part in designing and building the backend systems that drive their AI-powered patient engagement platform, as well as lead engineering initiatives to create scalable infrastructure and deploy machine learning solutions that deliver real-time impact on patient outcomes.


Responsibilities

• Develop and maintain scalable backend services and APIs that support the AI-driven platform.

• Design and manage infrastructure for deploying and monitoring LLM-based applications.

• Partner with ML engineers to integrate conversational AI and predictive models.

• Lead the architecture of a flexible backend system that grows with data and product demands.

• Establish and manage CI/CD pipelines, automated testing and deployment processes.

• Write secure, efficient and maintainable code in line with engineering best practices.

• Create reusable components and libraries to streamline development workflows.

• Leverage cloud services (GCP, Azure, AWS) to build scalable and cost-effective infrastructure.

• Conduct code reviews and help define engineering standards.

• Identify, troubleshoot, and resolve system performance and reliability issues.

Skillset

• At least 5 years of experience in full stack development, with a minimum of 2 years in a senior engineering role.

• Proven ability to build early-stage products from concept to launch, and scale them successfully.

• Proficient in Node.js, Python, React, Express and relational database technologies.

• Practical experience or strong enthusiasm for integrating LLMs into production environments.

• Expertise in designing scalable and maintainable system architectures.

• Solid understanding of Clean Code principles, test-driven development (TDD), and CI/CD workflows.

• Familiarity with Docker, Kubernetes, and modern DevOps practices.

• Knowledge of AI/ML deployment workflows, A/B testing frameworks, and monitoring tools.

• Demonstrated leadership in driving engineering projects to successful delivery.

• Industry experience in healthcare technology is a bonus.

Benefits

• Salary: $160k - $175k

• Equity.

• Remote and flexible working options.

• Health, dental and retirement package.

• Develop and sustain reliable systems for training, deploying and scaling AI models.
• Build and enhance workflows for data preparation, model training, evaluation and deployment.
• Identify and resolve performance bottlenecks to ensure smooth operation for thousands of users and contributors.
• Automate infrastructure provisioning, deployment and monitoring following DevOps best practices.
• Collaborate closely with researchers and developers, both within the company and across our open-source community.
• Contribute to the development and direction of their open-source platform and foundational AI models.

• Extensive experience in infrastructure engineering, DevOps or cloud-native environments.
• Deep understanding of machine learning principles and practical experience with end-to-end ML workflows.
• Proficient in Python and skilled in best practices for software development.
• Practical knowledge of cloud platforms such as AWS, Google Cloud or Azure.
• Experience with distributed computing and designing scalable systems.
• Enthusiasm for open-source development and active participation in community-driven projects.

• Salary: $100K - $220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.

• Lead research efforts in LLMs and VLMs, covering model development, evaluation, optimization and benchmarking.
• Shape the strategic direction of open-source AI/ML innovation within the organization’s  platform.
• Publish impactful research in leading academic venues.
• Build and nurture academic partnerships to strengthen the company’s global open research community.
• Mentor and guide team members, encouraging a culture rooted in scientific excellence and open collaboration.

• PhD degree in Computer Science or a related field, with a specialization in AI/ML.
• Proven track record of publications in leading AI/ML conferences and journals.
• Demonstrated leadership in driving research initiatives and managing complex technical projects.
• Expert-level proficiency in machine learning, with hands-on experience in PyTorch, LLMs and VLMs.
• Strong commitment to open source and a passion for building in the open through community collaboration.

• Salary: $160K–$220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.
• Hybrid working with offices in Seattle, WA and Palo Alto, CA.

• Design and build scalable, maintainable platform systems from the ground up.
• Develop robust backend services and APIs mainly with Python and using Rust for performance-critical components.
• Work closely with frontend teams on integrations using JavaScript and TypeScript.
• Automate infrastructure deployment using modern DevOps tools and Infrastructure as Code practices.
• Provide technical leadership by establishing best practices and guiding architectural decisions.
• Own features end-to-end, from initial concept through to production release.

• Proven experience in software development, with strong Python backend skills.
• Demonstrated success building systems from the ground up in fast-paced environments.
• Proficiency in JavaScript/TypeScript and modern frontend frameworks.
• Experience with Rust, or a willingness to learn it for performance-critical tasks.
• Hands-on familiarity with cloud platforms such as AWS, GCP or Azure.
• Experience with containerization using Docker and orchestration with Kubernetes.
• Strong system design skills, including designing clean APIs and scalable architectures.
• A DevOps mindset, with expertise in CI/CD pipelines, monitoring and observability.
• Excellent communication and teamwork skills.
• Passion for open-source and active contribution to community-driven projects.

• Salary: $100K - $220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.

• Architect, maintain and scale high-performance computing (HPC) and storage solutions across both on-premises and cloud environments.
• Collaborate with global teams to diagnose and resolve infrastructure challenges across operating systems, storage and networking.
• Champion innovation by exploring and implementing emerging technologies to enhance research infrastructure.
• Oversee and optimise a range of compute resources, including CPUs, GPUs and other specialised processing units.
• Work closely with software engineers to deliver seamless, high-performance platforms that power advanced research initiatives.

• Minimum of 5 years of experience in data engineering.
• Strong, hands-on experience with Databricks, especially in a production environment
• Solid expertise in Linux-based systems and environments.
• Hands-on experience with Infrastructure as Code tools, such as Ansible and Terraform.
• Working knowledge of cloud platforms like AWS, GCP or Azure.
• Genuine interest in high-performance computing and solving complex system-level challenges.
• Proven ability to diagnose and resolve issues across various layers of infrastructure.
• Effective communicator and team player, comfortable working in cross-functional and globally distributed teams.

• Salary: $250k - $300k.
• Performance Bonus.
• 401(k) matching up to 50%.
• Health, dental, vision, mental health, disability and life insurance.