Machine Learning Engineer

1 month ago


Brighton, United Kingdom 15gifts Full time
The Machine Learning Engineer will help develop/deploy AI-powered products as we embark on a journey to build a new AI-powered sales advisor.nThis is a mid level role, requiring at least 2-3 years of experience in relevant roles, and an academic background in computing or STEM subjects to at least undergraduate level.

The person we’re looking fornAside from technical expertise, key skills will include communication with stakeholders, ability to understand business requirements and the type of attention to detail that ensures thoroughness in product deployments.nResponsibilities and expertise will be in the field of ML and AI model deployment, monitoring, integration across the tech stack and making best use of data-focussed compute resources.nDiversity is incredibly important to us. Research shows how people from marginalised groups are less likely to apply for a job unless they meet every requirement. However, these accountabilities are a guide and, if you feel like this role could be for you and you don’t meet every criteria, please do apply. We’d love to hear from you.

You’ll be responsible fornDevelopment of a Conversational Recommendation System which utilises Large Language Models (LLMs) and other NLP technologiesnDeploying scalable and cost effective machine learning systemsnEvolving and maintaining our machine learning stacknMonitoring and analysing deployed models for performance and costsnMaking effective use of cloud infrastructure in our ML stack

Skills and experiencenFamiliar with the Python-based data science tech stacknPythonnDocker & KubernetesnAWS CloudnDeep learning frameworks - Pytorch and TensorflownHuggingFace ecosystem (optional)nOther machine learning frameworks - scikit-learn, XGboost, CatBoost etcnAbility to understand and develop state-of-the-art implementationsnFamiliarity with state-of-the-art deep learning (e.g. transformers) and reinforcement learning (e.g. RLHF), as well as optimised training procedures (e.g. QLora & Adapters)nComfortable with the machine learning lifecycle from research to deployment. This includes all things MLOps - model development, validation, deployment and monitoringnFamiliarity with state of the art NLP - text embeddings (representation learning), vector databases, large language models, machine translation, intent recognition, entity recognition, text classification etcnFamiliarity with recommendation engines - collaborative filtering, content-based, hybrids, graph & knowledge based etc (optional)nFamiliarity with CUDA and other hardware (GPU) acceleration for deep learning models (optional)

Diversity is incredibly important to us. Research shows how people from marginalised groups are less likely to apply for a job unless they meet every requirement. However, these accountabilities are a guide and, if you feel like this role could be for you and you don’t meet every criteria, please do apply. We’d love to hear from you.

Why choose usnOur CulturenOur success is underpinned by our cultural values. These values are not something we stick up on a wall – they don’t need to be. They are behaviours that we recognise and celebrate in each other. They are what we live by every day.nOur Cultural ValuesnPositive vibesnTake the initiativenSeek feedbacknStay aheadnTeam 15gifts

Our office and remote workingnWe can confidently say that our sea-view office is one of Brighton’s best. Whilst we see huge benefits to being able to collaborate and socialise together again, we’ve also learnt a lot about the benefits of working from home.

Benefits includenEmployee Assistance Programme (confidential counselling)nMedicash healthcare scheme (reclaim costs for dental, physiotherapy, osteopathy and optical care)neasitBrighton travel scheme (discounted public transport options)nCycle to work schemenLife Insurance schemen25 days holiday + bank holidays + your birthday off (rising to 28 after 3 consecutive years with the business & 30 after 5 years)nContributory pension scheme

Other extras in the officenOn site changing rooms, showers and internal bike storagenBreakfast, fresh fruit, snacks, beersnYoga and other fitness activitiesnRegular social events, including Friday drinks



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