Machine Learning Engineer (Life Sciences)

TL;DR

Machine Learning Engineer (Life Sciences): Building and deploying production-grade ML software, tools, and infrastructure with an accent on creating reusable, scalable solutions and defining best practices. Focus on collaborating with cross-functional teams and clients to ensure technical feasibility and timely delivery of high-quality ML systems.

Location: Hybrid: 2 days in office in London, UK

Company

hirify.global is an AI company established in 2014, focused on transforming performance through human-centric AI solutions for various global customers including government, finance, retail, energy, life sciences, and defence sectors.

What you will do

• Build and deploy production-grade ML software, tools, and infrastructure.
• Create reusable, scalable solutions to accelerate ML systems delivery.
• Collaborate with engineers, data scientists, and commercial leads to solve critical client challenges.
• Lead technical scoping and architectural decisions to ensure project feasibility and impact.
• Define and implement hirify.global’s standards for deploying machine learning at scale.
• Act as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.

Requirements

• Understanding of the full machine learning lifecycle and experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
• Strong Python skills and solid experience in software engineering best practices.
• Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
• Experience with container and orchestration tools such at Docker & Kubernetes.
• Comfortable with core ML concepts, including probability, statistics, and common learning techniques.
• Excellent communication skills, able to guide technical teams and confidently advise non-technical stakeholders.

Culture & Benefits

• Unlimited Annual Leave Policy.
• Private healthcare and dental.
• Enhanced parental leave.
• Family-Friendly Flexibility & Flexible working.
• Sanctus Coaching.
• Hybrid working (2 days in our Old Street office, London).

Hiring process

• Talent Team Screen (30 minutes)
• Pair Programming Interview (90 minutes)
• System Design Interview (90 minutes)
• Commercial Interview (60 minutes)