Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Skills Alliance
Liverpool
6 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Develop novel cell embeddings that integrate multi-omics foundation models— transcriptomics, proteomics, epigenomics, and metabolomics—to capture comprehensive cellular signatures. Your work will enable precise predictions of drug effects, driving innovation in drug discovery.


Key Responsibilities:

Model Development:Design deep learning models integrating diverse omics data to create robust cell embeddings for digital twin technology.

Multi-Omics Integration:Develop and refine foundation models across omics platforms into a unified cell representation.

Collaboration:Work with experts in bioinformatics, drug discovery, and AI to validate models and integrate multi-modal data.

Client & Partner Engagement:Support product and service teams in translating AI models into real-world drug discovery applications.

Research Leadership:Stay at the forefront of AI and omics advancements, contributing to scientific publications and innovation.


Preferred Qualifications:

1.PhD/Postdoc in Computer Science (or related fields): Publications in top ML conferences (e.g., NeurIPS, ICLR, ICML, CVPR).

2.Strong ML/Applied Math Background:Expertise in advanced ML techniques.

3.Deep Learning Experience:Building and scaling AI models for omics or high dimensional biological data.

4.Multi-Omics Integration: Experience developing foundation models across omics datasets.

5.Collaborative Mindset:Track record of success in interdisciplinary teams and cross-functional projects.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.