Beamery

About the Company

Beamery's AI talent platform empowers companies to understand the skills and capabilities they have, build more agile workforce plans, and attract, retain, upskill and redeploy their workforce. With Beamery, organizations are able to navigate change at speed, retain critical skill sets, foster diversity, and build the workforce of the future.

Listed Jobs

Company Name

Beamery

Job Title

Senior AI Engineer

Job Description

**Job Title:** Senior AI Engineer **Role Summary:** Design, develop, and operate next‑generation AI services, APIs, and data‑science models. Drive end‑to‑end project delivery—from discovery and prototyping to implementation, performance measurement, and production operations—while collaborating closely with MLOps, product, and design teams in an agile environment. **Expectations:** - Scale and productize machine‑learning models for both batch and real‑time use. - Deliver high‑quality, production‑ready code using Python and its ecosystem. - Utilize containerization (Docker) and orchestration (Kubernetes) for reliable deployments. - Communicate clearly with cross‑functional stakeholders and contribute to continuous process improvement. - Foster an inclusive, collaborative team culture and participate in diversity initiatives. **Key Responsibilities:** - Architect and implement core AI services and APIs. - Build, train, and optimize ML models, ensuring they meet performance and fairness criteria. - Partner with MLOps to enhance model deployment pipelines, monitoring, and alerting. - Lead projects from concept through rollout, measuring impact and iterating as needed. - Produce and maintain technical documentation and support agile sprint planning. - Engage with product managers and designers to align AI solutions with customer value. **Required Skills:** - Strong proficiency in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit‑learn). - Experience scaling and productizing ML models for offline batch and online real‑time services. - Hands‑on expertise with Docker and Kubernetes for containerized deployments. - Knowledge of MLOps/LLMOps practices, CI/CD, and model monitoring. - Excellent problem‑solving, communication, and teamwork abilities. - Curiosity-driven approach with a focus on understanding underlying business and technical requirements. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Engineering, Data Science, AI, or a related field (Master’s or Ph.D. preferred). - Relevant certifications (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer, Kubernetes Administrator) are a plus but not mandatory.

London, United kingdom

Remote

Senior

12-09-2025