Machine Learning Engineer
1 month ago
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.
This 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 for
Aside 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.
Responsibilities 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.
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.
You’ll be responsible for
- Development of a Conversational Recommendation System which utilises Large Language Models (LLMs) and other NLP technologies
- Deploying scalable and cost effective machine learning systems
- Evolving and maintaining our machine learning stack
- Monitoring and analysing deployed models for performance and costs
- Making effective use of cloud infrastructure in our ML stack
Skills and experience
- Familiar with the Python-based data science tech stack
- Python
- Docker & Kubernetes
- AWS Cloud
- Deep learning frameworks - Pytorch and Tensorflow
- HuggingFace ecosystem (optional)
- Other machine learning frameworks - scikit-learn, XGboost, CatBoost etc
- Ability to understand and develop state-of-the-art implementations
- Familiarity 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)
- Comfortable with the machine learning lifecycle from research to deployment. This includes all things MLOps - model development, validation, deployment and monitoring
- Familiarity with state of the art NLP - text embeddings (representation learning), vector databases, large language models, machine translation, intent recognition, entity recognition, text classification etc
- Familiarity with recommendation engines - collaborative filtering, content-based, hybrids, graph & knowledge based etc (optional)
- Familiarity 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 us
Our Culture
Our 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.
Our Cultural Values
- Positive vibes
- Take the initiative
- Seek feedback
- Stay ahead
- Team 15gifts
Our office and remote working
We 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 include
- Employee Assistance Programme (confidential counselling)
- Medicash healthcare scheme (reclaim costs for dental, physiotherapy, osteopathy and optical care)
- easitBrighton travel scheme (discounted public transport options)
- Cycle to work scheme
- Life Insurance scheme
- 25 days holiday + bank holidays + your birthday off (rising to 28 after 3 consecutive years with the business & 30 after 5 years)
- Contributory pension scheme
Other extras in the office
- On site changing rooms, showers and internal bike storage
- Breakfast, fresh fruit, snacks, beers
- Yoga and other fitness activities
- Regular social events, including Friday drinks
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