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

Robotics Software Engineer

Job Description

Job Title: Robotics Software Engineer Role Summary: Design, develop, and maintain production‑level software for robotic manipulators and mobile platforms, focusing on motion planning, perception, and navigation. Collaborate within a multidisciplinary team to deliver reliable, high‑performance code that operates on physical robots and simulation environments. Expectations: - Deliver clean, modular, production‑ready code. - Adhere to Agile methodologies (Scrum/Kanban) and CI/CD pipelines. - Participate in full development cycle: design, implementation, testing, deployment. - Continuously improve code quality, performance, and reliability. Key Responsibilities: - Build motion control, kinematics, dynamics, and motion planning modules. - Integrate and calibrate RGB/Depth cameras and LiDAR sensors. - Develop navigation, localisation, and mapping solutions for robotic platforms. - Write and maintain ROS2 nodes, Docker containers, and associated tooling. - Use Git (Gitflow), perform code reviews, and manage tasks in Jira. - Conduct unit, integration, and system testing; contribute to CI/CD pipelines. - Collaborate on sprints, stand‑ups, retrospectives, and backlog refinement. Required Skills: - 3+ years of production‑level software engineering, preferably in robotics. - Proficient in Python and C++ with scientific/numerical libraries. - Experience with ROS2, Docker, Linux development, and CI/CD. - Deep knowledge of robotic kinematics, dynamics, control, and motion planning. - Familiarity with sensor integration (RGB, depth, LiDAR) and ROS2 sensor drivers. - Solid understanding of object‑oriented design and SOLID principles. - Agile experience (Scrum preferred); Jira and Confluence usage. - Strong teamwork, communication, and problem‑solving abilities. Required Education & Certifications: - Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience). - No specific certifications required, but knowledge of ROS, Agile, and Linux is essential.

London, United kingdom

Hybrid

04-11-2025

Company Name

Cubiq Recruitment

Job Title

Machine Learning Researcher | Protein Engineering | Pre-seed startup

Job Description

**Job Title** Machine Learning Researcher – Protein Engineering (Pre‑seed Startup) **Role Summary** Lead the AI‑driven protein design pipeline in a fast‑moving early‑stage biotech startup. Drive end‑to‑end development of protein language models (PLMs), integrate deep mutational scanning (DMS) data, build machine‑learning‑directed evolution (MLDE) toolkits, and spearhead large‑scale pre‑training efforts. Collaborate closely with experimental biologists to validate predictions and shape the company’s BioAI strategy, with potential progression to a co‑founder or leadership role. **Expectations** - Own the design, training, and deployment of PLMs for de novo protein generation. - Integrate DMS data to enhance model accuracy and reliability. - Build and adapt MLDE frameworks to accelerate experimental discovery. - Lead large‑scale pre‑training of transformer models (tens of billions of parameters). - Bridge computational work with wet‑lab validation, ensuring actionable insights. - Innovate independently, proposing novel approaches and guiding research direction. - Operate effectively in a small, high‑velocity team with on‑site London presence. **Key Responsibilities** - Fine‑tune and deploy protein language models for protein generation and optimisation. - Incorporate DMS data and PLM embeddings to improve predictive performance. - Develop and maintain MLDE toolkits for directed evolution workflows. - Orchestrate large‑scale PLM pre‑training pipelines and manage compute resources. - Collaborate with experimental biologists to validate predictions and iterate designs. - Mentor junior team members and contribute to research publications and patents. - Communicate findings to stakeholders and influence product strategy. **Required Skills** - Expertise in machine learning, computational biology, or bioinformatics. - Proven experience in protein sequence modelling, representation learning, and generative modelling. - Proficiency with PyTorch or TensorFlow and modern transformer architectures. - Hands‑on experience with PLM fine‑tuning, MLDE, or related pipelines. - Ability to translate computational outputs into experimentally testable hypotheses. - Strong coding, data engineering, and model optimisation skills. - Creative, self‑directed thinker with a track record of independent research. **Required Education & Certifications** - PhD or equivalent professional experience in machine learning, computational biology, or bioinformatics. - Demonstrated publication record or equivalent evidence of high‑level research output.

London, United kingdom

On site

10-11-2025

Company Name

Cubiq Recruitment

Job Title

Machine Learning Engineer

Job Description

**Job Title** Machine Learning Engineer **Role Summary** Lead the design, development, and validation of anomaly‑detection algorithms for bacterial genomes to improve diagnostic accuracy in bloodstream infection tests. Work in an autonomous, research‑oriented team focused on rapid iteration and scientific exploration. **Expectations** - Deliver high‑impact, interpretable ML models within a clinical diagnostics pipeline. - Translate proprietary genomic data into robust, benchmarked solutions with measurable real‑world effect. - Conduct fast, experimental research cycles, prioritize ideas by empirical results, and maintain clear communication across bioinformatics, microbiology, and software teams. **Key Responsibilities** - Design and implement bespoke deep‑learning and statistical anomaly‑detection models for bacterial genomes. - Develop, train, and benchmark transformer‑based and foundation‑model architectures for genome representation. - Analyze large proprietary genomic datasets to ensure robustness and interpretability. - Generate synthetic and real‑world data for validation and testing. - Deliver prototype code to external partners, gather feedback, and iterate. - Contribute to broader R&D activities such as statistical framework design and data infrastructure. - Collaborate closely with bioinformatics, microbiology, and software teams to integrate models into the diagnostic pipeline. **Required Skills** - Strong Python programming, with expertise in PyTorch, TensorFlow, or scikit‑learn. - Proven experience applying ML to biological or genomic data, including working with large or complex datasets. - Familiarity with genome assembly, QC, annotation, and standard bioinformatics workflows. - Knowledge of model evaluation, benchmarking, and explainability techniques. - Ability to design, prototype, and iterate experiments independently. - Excellent communication and cross‑functional collaboration skills. **Required Education & Certifications** - MSc or PhD in Machine Learning, Computational Biology, Bioinformatics, or a related discipline (or equivalent industry experience). ---

London, United kingdom

Remote

17-11-2025

Company Name

Cubiq Recruitment

Job Title

Member of Technical Staff

Job Description

**Job Title** Member of Technical Staff – Applied Machine Learning (Agentic AI) **Role Summary** Design, build, and ship large‑scale agentic AI systems that enable enterprises to move from experimentation to production with minimal ML engineering overhead. Work across the stack—from data pipelines and model training to real‑time inference and deployment—while collaborating directly with founders on architecture, strategy, and product roadmap. **Expectations** - Deliver end‑to‑end agentic AI solutions that are production‑ready and scalable. - Bridge research and engineering: translate novel concepts into robust, shipping code. - Operate at startup velocity; iterate quickly, ship frequently, and adapt to changing requirements. - Act as an early technical leader, influencing architecture, standards, and best practices. - Maintain high code quality, testing, and documentation for sustainability. **Key Responsibilities** - Design and implement intelligent orchestration layers and large‑scale agentic architectures. - Build and optimize training pipelines, streaming data ingestion, and real‑time inference systems. - Deploy models to production using containerized or serverless platforms; manage scalability and latency. - Create tooling that accelerates ML team experimentation, deployment, and monitoring. - Collaborate with founders and product teams on roadmap, strategy, and technical trade‑offs. - Contribute to a low‑ego, shipping‑centric culture; mentor peers and drive engineering excellence. **Required Skills** - Deep experience in applied machine learning, especially agentic AI, LLM engineering, and planning & reasoning. - Proficient with Python, PyTorch, JAX, Ray, and other modern ML stacks; comfortable with distributed training and inference. - Strong background in scalable ML infrastructure, data pipeline design, and production deployment (cloud, Kubernetes, Docker). - Hands‑on knowledge of reinforcement learning (RLHF/RLAIF), simulation, and feedback‑driven adaptation. - Proven ability to ship high‑quality code quickly and iterate on real‑world problems. - Builder mindset: thrive on turning concepts into operational systems. - Experience in early‑stage or startup environments is a plus. **Required Education & Certifications** - Bachelor’s (or higher) degree in Computer Science, Engineering, Machine Learning, or related field. - No mandatory certifications required; relevant machine‑learning or cloud platform certifications may be advantageous.

London, United kingdom

Hybrid

17-11-2025