Senior Machine Learning Engineer

This is a dynamic and highly rewarding position for someone who is passionate about using the latest technology and science to deliver patient outcomes and building an innovative company from the ground up.

We are a techbio food as medicine pre-seed company on a mission to help 1 million people gain 5 years of healthy living by 2030. We intend to become the category leaders in musculoskeletal self-care.

We help osteoarthritis patients self-manage their condition through an app offering end-to-end support. We use the latest AI, biomarker profiling and precision medicine science to deliver plans that help patients with osteoarthritis reduce their pain levels, improve mobility and potentially even slow down the progression of this debilitating disease affecting over 528 million people worldwide. We will be launching our first NHS pilot in Q4 and have a growing product waitlist.

Healthnix is led by an outstanding team of UCL, Oxford and Imperial College scientists, engineers, and entrepreneurs, and backed by a very experienced C-Suite, NHS and a top research advisory board. We have already secured initial funding and are now preparing for the larger institutional raise in Q4 2024. This is an exciting opportunity to join a rocket ship & a category defining company before we fully take off.

Job Summary

We're seeking a trailblazing Senior Data Scientist/ML Engineer to revolutionize our recommendation and personalization solutions. In this role, you'll leverage cutting-edge machine learning to build high-performance models that drive business value and transform user experiences. As a key player in our growing team, you'll have the unique opportunity to chart your own path, diving deep into recommendations, generative AI, NLP, and system design. You'll own the entire ML stack, serving as both a technical leader and a subject matter expert, applying your industry knowledge to supercharge our products. If you're passionate about pushing the boundaries of AI and turning complex data into game-changing solutions, this is your chance to make a lasting impact. Join us and help shape the future of personalized technology.

Key Responsibilities

Apply state-of-the-art machine learning techniques, including deep learning, reinforcement learning, causal inference, and optimization, to design and build recommendation models & personalization engines tailored to our users' preferences.

Create the tools, frameworks and libraries that enable the acceleration of our ML product delivery.

Drive improvements to our current AI workflows in terms of process, performance and testing.

Proven experience setting up and optimizing retrieval-augmented generation (RAG) pipelines.

Present findings, insights, and solutions to the product team, translating complex technical concepts into business language.

Participate in the full software development cycle: design, develop, QA, deploy, experiment, analyze and iterate.

Mentor junior engineers and foster a collaborative, innovative team environment.

Establish thought-leadership by following up around state of the art research in responsible AI and Gen AI, experiment with and benchmark novel techniques related to model monitoring, model explainability, model fairness etc. Identify ways to leverage some of these into product offerings and guide efforts to pursue these.

Required Qualifications

Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field

5+ years of industry experience in building and deploying machine learning models, with a focus on recommendation systems and personalization engines

Hands-on experience in delivering machine learning models to production at scale

Experience in writing production-quality Python code

Comfortable working with Python data science and machine learning libraries such as scikit-learn, TensorFlow, Keras, pandas, numpy, PyTorch, XGBoost

Experience with common LLM frameworks (Langchain, Llamaindex, RAG, HuggingFace, and eval frameworks like Ragas or Presidio)

Strong understanding of machine learning applications development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring and alerting

Comfortable working with Docker and containerised applications

Experience with A/B testing and experimentation in a production environment

Preferred Qualifications

Experience in a customer-facing role, including gathering requirements and providing data-driven insights

Knowledge of cloud platforms (AWS, GCP, or Azure) for deploying machine learning models at scale

Prior work with Agentic Workflows

Experience speaking at industry events

Familiarity with data privacy regulations and best practices in handling sensitive user data

Relevant certifications such as Certified Data Scientist, Google Cloud Professional Data Engineer, or AWS Certified Machine Learning – Specialty

Soft Skills

Strong analytical and problem-solving abilities

Excellent verbal and written communication skills

Ability to work effectively in a team environment

Self-motivated with a passion for continuous learning

Customer-oriented mindset with strong interpersonal skills

Location and team

You are ideally based in London, but we are open to remote candidates

You will be joining a team of 4, including two co-founders, a full stack founding engineer and a scientist