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🔥 We challenge you!
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We seek a versatile Full-stack MachineLearning Engineer with a strong background in machine learning and a hands-on approach to building scalable, distributed AI systems. You will play a key role in developing and integrating LLMs and AI-driven solutions into real-world applications, transforming data usage and sharing in healthcare—starting with clinical trial patient recruitment.
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Beyond just developing models, you thrive in end-to-end problem-solving, from data preparation and model optimization to deploying and maintaining AI-driven products. You are comfortable working across different layers of the tech stack, ensuring that AI solutions are built effectively, integrated, and scaled.
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👉🏼 You are
We are looking for someone who:
- Enjoys tackling technical challenges across multiple domains, optimising machine learning pipelines, building robust APIs, or scaling cloud infrastructure.
- Thrives in a fast-paced startup environment where priorities shift, and taking ownership is key.
Has a proven track record of delivering real-world AI applications—not just research, but functional products that users rely on.
- Is entrepreneurial, ambitious, and unafraid to step outside their comfort zone to solve problems that drive impact.
If you're excited about shaping AI-powered healthcare solutions and want to work on the entire lifecycle of AI development, from research to production, we'd love to hear from you!
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👩‍💻 Requirements
MS/BS in Computer Science, AI, Statistics, or a related field, or equivalent experience, with 2+ years of industry experience in machine learning.
Strong analytical and debugging skills, willing to work outside your comfortzone and learn.
Proactive, independent, and organized, able to take ownership of tasks and drive them to completion with minimal supervision.
Comfortable working in a small, fast-paced startup environment, taking on multiple roles when needed.
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Proven experience developing, optimizing, and deploying ML models in production environments.
Strong programming skills in Python and TypeScript.
Extensive experience with ML frameworks such as PyTorch and TensorFlow.
Experience building scalable APIs and backend services, preferably using FastAPI, Express, or similar frameworks.
Experience with HTML, CSS, and JavaScript, and working with a modern JavaScript framework like React, Vue, or Svelte.
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Hands-on, adaptable, and eager to work across multiple areas of engineering rather than being limited to a single specialization.
Experience with federated learning frameworks such as vantage6, Nvidia FLARE, or Flower (preferred).
Experience with large language models (LLMs), fine-tuning, and retrieval-augmented generation (RAG) (preferred).
Knowledge of efficient data processing techniques, scalable data storage, and vector databases (preferred).
Experience designing high-performance, distributed systems for AI applications(preferred).
Experience with architecting and building distributed systems (preferred).
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Hands-on experience with cloud providers like AWS, GCP, or Azure (preferred).
Some experience working with Infrastructure-as-Code tools like Terraform(preferred).
Understanding of CI/CD pipelines, containerization (e.g., Docker, Podman), and orchestration (e.g., Kubernetes) for deploying AI models and applications(preferred).
Familiarity with at least one compiled language, such as Go, Java, or C++(preferred).
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🏦 What do you get in return?
- Competitive Salary
- Access to the latest technologies, tools, and devices necessary to develop cutting-edge solutions.
- Experience working at a fast-growing, early-stage startup where you can express, explore and grow your talents and interests in numerous areas
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