allica-bank - Senior MLOps Engineer - FTC
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Requirements
• We strongly value talent, agency, curiosity, and hunger. • Strong technical ability in machine learning, NLP, or large language models. • Hands-on experience with Python, PyTorch/TensorFlow, and OpenAI SDK (or similar). • Strong knowledge of Classification and Time series models. • Experience shipping LLM applications in production. • Contributions to ML/AI projects and/or a portfolio of ML projects you’ve worked on. • Achievements in competitive programming, STEM olympiads, or other indicators of exceptional technical ability. • Peer-reviewed publications. • Please note: This is a 12 month fixed term role with possibility to extend longer. • Working at Allica Bank • At Allica Bank we want to ensure our employees have the right tools and environment in which to succeed in their role and in support of our customers. • Our employees are at the heart of everything we do, so our benefits are designed with you in mind: • Full onboarding support and continued development opportunities • Options for flexible working • Regular social activities • Pension contributions • Discretionary bonus scheme • Private health cover • Life assurance • Family friendly policies including enhanced Maternity & Paternity leave • Don’t tick every box? • Don’t worry if you don’t have all the skills or requirements listed on the job description. If you think you’ll be a good fit, we’d still love to hear from you! • Flexible working • We know the ‘9-to-5’ isn’t right for everyone. That’s why Allica Bank is fully committed to flexible and hybrid working. Please let us know what is best for you and, if we can, we will do our best to accommodate. • We’re a diverse bunch here at Allica, with all kinds of experiences, backgrounds and lifestyles. Our openness and differences make us stronger, and we want everybody to feel comfortable bringing as much of themselves to work with them as they like.
Responsibilities
• Build and deploy ML and LLM-powered applications that deliver actionable financial insights and decision support. • Work end-to-end across the stack: rapidly prototype and iterate with product and design to bring new features to life. • Ensure models interpretability and explainability, so SMEs can understand the “why” behind the insights. • Develop guardrails and fail-safes to guarantee AI outputs are trustworthy in high-stakes financial contexts.
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