Cubiq Recruitment

About the Company

We believe that advanced technology is paving the way to a more sustainable future.

We believe in going the extra mile to provide our customers with a competitive edge.

Since our inception in 2010, Cubiq has established a reputation for excellence in the delivery of high quality engineering talent to the most ground-breaking technology companies in the world.

Cubiq methods are subtle, data-driven, and highly effective, which is how we have become widely recognised as leading experts within engineering and technology recruitment.

By fostering a culture of systematic improvement throughout every area of our business, we are able to provide a premium service that evolves around you.

We deliver across the following fields:

Executive
Aerospace
Data & Analytics
Design, Development, and QA
Security, Cloud, & Infrastructure
Projects, Change, & Transformation
Commercial & Operations
Embedded & Electronics
Mechanical
Electrical
Systems
Quality

When it comes to linking 'best in class' engineers with companies developing world-changing products and services, it's all about quality, accuracy, and timing.

To achieve this, you need a recruitment partner that you can trust to deliver.

Call the team on +44 161 214 3842 / +447485321291 for a consultation or email enquiries@cubiqrecruitment.com for further details on our services.

Listed Jobs

Company Name

Cubiq Recruitment

Job Title

Artificial Intelligence Engineer

Job Description

**Job Title:** Artificial Intelligence Engineer **Role Summary** Advance original foundation model research and engineering from first principles, designing novel architectures, and implementing training/alignment systems to push AI capabilities. **Expectations** Candidates must demonstrate independent, first-principles problem-solving and a drive to innovate rather than iterate on existing systems. Ideal for engineers/researchers seeking high-ownership roles in low-bureaucracy environments. **Key Responsibilities** - Design and train foundation models using large-scale, multimodal datasets. - Lead post-training techniques (supervised fine-tuning (SFT), reinforcement learning with human feedback (RLHF), reward modeling, direct preference optimization (DPO)). - Build scalable data curation pipelines, filtering tools, and evaluation frameworks. - Experiment with personalization, representation learning, and preference modeling. - Transition research prototypes into production-ready systems in a collaborative team. **Required Skills** - Expertise in large-scale training, multimodal modeling, reinforcement learning (RL), and large language models (LLMs). - Hands-on experience with alignment methodologies, optimization techniques, and model architecture design. - Proficiency in Python, PyTorch/TensorFlow, and building machine learning pipelines. - Strong analytical skills for experimental design and iterative system development. **Required Education & Certifications** Advanced degree in Computer Science, Artificial Intelligence, or related field preferred (MS/PhD). Equivalent industry experience may substitute. **Certifications:** Not specified.

London, United kingdom

On site

15-12-2025

Company Name

Cubiq Recruitment

Job Title

Software Engineer

Job Description

**Job Title:** Software Engineer **Role Summary:** Design, develop, and maintain high‑performance backend services and APIs that enable scientific AI initiatives. Own the full software lifecycle—from architecture and implementation to testing, deployment, and observability—while collaborating with data engineers, AI scientists, and domain experts in a fast‑moving R&D environment. **Expectations:** - Deliver reliable, scalable, and secure software solutions on schedule. - Ensure code quality, documentation, and adherence to engineering best practices. - Communicate system designs and decisions clearly across multidisciplinary teams. - Operate autonomously while contributing to a growing ML infrastructure team. **Key Responsibilities:** - Build backend services, REST/gRPC APIs, and modular components for scientific applications. - Integrate ML inference services, hardware interfaces, and data pipelines with high availability and low latency. - Manage end‑to‑end production lifecycle: design, development, automated testing, benchmarking, deployment, and monitoring. - Develop and maintain CI/CD pipelines and reproducible development workflows. - Promote security, observability, and robust operational practices. - Collaborate closely with data engineers, AI scientists, software engineers, and domain experts. **Required Skills:** - Proficiency in Python; experience building distributed, production‑grade systems. - Strong background in API design (REST, gRPC) and microservice architectures. - Hands‑on experience with CI/CD tools, containerization (Docker) and orchestration (Kubernetes preferred). - Ability to design and operate scalable data infrastructure, hardware interfaces, and ML model serving. - Experience with observability, automated testing, and performance benchmarking. - Excellent teamwork and communication skills within multidisciplinary groups. **Required Education & Certifications:** - MSc (or equivalent practical experience) in Computer Science, Software Engineering, or a related technical field. - Proven professional experience as a Software Engineer (significant, not entry‑level).

Oxford, United kingdom

Hybrid

18-12-2025

Company Name

Cubiq Recruitment

Job Title

ML Engineer | Pre-seed startup | Protein / Molecules

Job Description

Job Title: ML Engineer – Protein & Molecule AI Role Summary: Design, develop, and deploy machine‑learning models for molecular and protein data, integrating them into a production pipeline that supports experimental biology teams. Expectations: Deliver scalable ML solutions quickly, collaborate directly with chemists and biologists, and maintain high code quality in a fast‑moving startup environment. Key Responsibilities: - Build and maintain end‑to‑end ML infrastructure for large‑scale training, inference, and deployment. - Implement generative models, representation learning, and geometric deep learning techniques on protein/molecule datasets. - Optimize models for performance and resource efficiency in cloud or on‑premise settings. - Translate experimental requirements into model specifications and validate outputs with domain experts. - Monitor model performance in production and iterate based on real‑world feedback. - Write clear documentation and unit tests; facilitate continuous integration/continuous deployment (CI/CD). - Mentor junior team members and share best practices in ML engineering. Required Skills: - Proficiency in Python, PyTorch/TensorFlow, and CUDA. - Experience with large‑scale data pipelines (e.g., Apache Spark, Dask). - Knowledge of ML infrastructure tools (MLflow, Kubeflow, Docker, Kubernetes). - Strong foundation in modern ML: generative modeling, representation learning, geometric deep learning. - Familiarity with bioinformatics/molecular datasets (proteins, small molecules, structural data). - Excellent problem‑solving, code‑review, and communication skills. - Ability to thrive in a remote, cross‑disciplinary, rapid‑iteration setting. Required Education & Certifications: - Bachelor’s or higher degree in Computer Science, Data Science, Bioinformatics, or related field. - Relevant certifications (e.g., TensorFlow Developer, AWS Certified Machine Learning, Google Cloud ML Engineer) are a plus but not mandatory.

London, United kingdom

Remote

29-01-2026

Company Name

Cubiq Recruitment

Job Title

Head of ML platform | AI Drug Discovery

Job Description

**Job Title** Head of ML Platform, AI Drug Discovery **Role Summary** Senior scientific and technical leader responsible for developing and scaling the computational platform for antibody and small‑molecule drug discovery. Leads cross‑functional teams of AI researchers, domain experts, and software engineers to translate biophysical requirements into production‑ready models, tools, and workflows, while positioning the organization at the forefront of AI for biologics. **Expectations** - Define and execute the computational strategy for antibody or small‑molecule design. - Own end‑to‑end development of biologics‑specific AI models and pipelines. - Serve as the internal subject‑matter expert on antibody structure, immune repertoire modeling, and biologics R&D. - Act as the technical liaison with strategic partners, scientific advisors, and cross‑functional stakeholders. - Drive continuous adoption of cutting‑edge research in AI for biologics. - Contribute to long‑term growth of the platform and the team. **Key Responsibilities** 1. Lead the scientific and technical development of the biologics/SM design platform. 2. Translate antibody‑specific requirements into computational tools, models, and workflows. 3. Collaborate closely with AI, software engineering, and drug design teams. 4. Serve as the internal SME on antibodies, immune repertoire modeling, and biologics R&D. 5. Interface technically with strategic partners and scientific advisors. 6. Keep the team ahead of emerging AI research in biologics and guide internal adoption. 7. Mentor and grow cross‑functional talent as the organization scales. **Required Skills** - Deep understanding of antibody structure/function (paratope/epitope mapping, affinity maturation, developability). - PhD or equivalent expertise in Computational Biology, Structural Bioinformatics, Biophysics, or related field. - Proven experience applying AI, machine learning, or physics‑based methods to biologics modeling or design. - Strong software fluency (Python, structural biology toolkits, ML frameworks). - Demonstrated ability to lead cross‑functional scientific/technical projects. - Excellent communication skills for both technical and non‑technical audiences. **Required Education & Certifications** - PhD (or equivalent) in Computational Biology, Structural Bioinformatics, Biophysics, or related discipline. ---

London, United kingdom

Hybrid

03-02-2026