Quotient Sciences

About the Company

Quotient Sciences is a drug development and manufacturing accelerator providing integrated programs and tailored services across the entire development pathway. Cutting through silos across a range of drug development capabilities, we save precious time and money in getting drugs to patients. Everything we do for our customers is driven by an unswerving belief that ideas need to become solutions, molecules need to become cures, fast. Because humanity needs solutions, fast. We employ over 1,300+ staff and operate from state-of-the-art manufacturing and clinical facilities in the US and UK. Our people make Quotient Sciences a special place to work. We are a dedicated team passionate about innovating and transforming drug development to help our customers develop new medicines for patients in need. We recruit people that are committed to making a difference, who excel at customer service and are always willing to go the extra mile. Teamwork is integral to our culture and success — helping, supporting and mentoring run through our DNA. Expect to join an empowering and innovative culture, where we encourage continuous improvement and offer opportunities to learn and develop every day.

Listed Jobs

Company Name

Quotient Sciences

Job Title

Machine Learning Engineer

Job Description

Job Title: Machine Learning Engineer Role Summary: Own the complete AI lifecycle for drug development, including data ingestion, model design, deployment, and monitoring. Deliver production‑grade machine‑learning solutions that accelerate therapeutic discovery and comply with regulatory standards. Act as a technical lead, ensuring responsible AI practices and fostering collaboration across product, engineering, and business teams. Expectations: - Achieve measurable business impact through AI solutions tied to strategic objectives. - Maintain high standards of model governance, compliance, and responsible AI. - Mentor junior staff and actively contribute to organizational best practices. Key Responsibilities: - Design, develop, and deploy AI/machine‑learning models for business challenges. - Evaluate, select, and tune modeling approaches balancing performance, interpretability, and operational fit. - Build scalable ML pipelines and infrastructure for classical ML and deep learning. - Deploy models to production via containerisation, CI/CD, and MLOps frameworks. - Develop LLM‑based tools using prompt engineering, retrieval, and embedding pipelines. - Create APIs, microservices, or workflow components to integrate AI tools. - Set up monitoring for drift, performance, latency, and failures; uphold logging and observability. - Embed responsible AI, governance, and compliance (GxP, validation) throughout all solutions. - Translate business requirements into technical specifications and deliver clear documentation. - Communicate complex technical concepts to both technical and non‑technical stakeholders. Required Skills: - Proven experience in AI engineering, machine learning, or data science with production‑grade model deployment. - Proficiency in Python, and frameworks such as TensorFlow, PyTorch, Scikit‑learn; or R. - Experience with cloud ML platforms (AWS SageMaker, MLflow) and CI/CD tooling. - Knowledge of monitoring, logging, and observability for ML systems. - Familiarity with LLMs, vector search, retrieval‑augmented systems. - Understanding of responsible AI, data governance, and regulatory compliance. - Agile experience (Kanban/Scrum) and familiarity with Jira or similar tools. - Strong communication and stakeholder‑management skills. Required Education & Certifications: - Bachelor’s degree or higher in Computer Science, Data Science, Bioinformatics, or closely related field (or equivalent experience). - Certifications in cloud ML or data engineering (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer) are advantageous. ---

Nottingham, United kingdom

On site

Senior

17-03-2026