Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
As a Senior Machine Learning Engineer, you'll take ownership of designing, building, and deploying advanced NLP systems and LLMs. You'll experiment, iterate, and build quickly, working alongside a cross-functional team in a dynamic, fast-fail environment. Your work will have a direct impact on our product and business as we push the boundaries of what's possible with AI
What you will be Doing
Build & Iterate Fast: Design, experiment, and deploy state-of-the-art NLP and LLM models. Quickly test hypotheses, optimise, and iterate based on real-world feedback.
Lead Innovation: Push the envelope with cutting-edge NLP techniques and models (transformers, GPT, BERT, etc.) to solve challenging problems in language understanding, generation, extraction, and more.
Shape the Product: Collaborate with engineers, product teams, and business leaders to align machine learning capabilities with product goals.
Fail Fast, Learn Fast: Drive rapid experimentation and maintain a learning-oriented mindset to pivot quickly when necessary.
Scale and Optimise: Take models from prototypes to production, optimising for performance, scalability, and efficiency.
Requirements
What type of person fits the role : Experience: 6+ years in machine learning, with deep expertise in NLP and LLMs/SLMs
LLMs: Strong knowledge of large language models (LLMs) and experience with frameworks and libraries like Hugging Face, OpenAI API, LangChain, DeepSpeed, LlamaIndex, LiteLLM, vLLM, etc.
Experience in model deployment and optimisation for inference speed and scalability is a plus.
Prompt Engineering: Proven ability to design and optimise prompts for LLMs, including techniques like few-shot, zero-shot, chain-of-thought, and prompt tuning.
RAG: Hands-on experience with Retrieval-Augmented Generation (RAG) to improve model performance in tasks such as question answering and document retrieval.
Skills: Strong Python skills, experience with cloud ML platforms (AWS preferred), and ML frameworks (PyTorch, TensorFlow). Familiarity with Docker and Kubernetes for containerisation and deployment.
Mindset: Entrepreneurial attitude with a "Build Fast, Fail Fast" approach, thriving in agile, iterative environments.
Benefits & conditions
Every person in our global team is valued for the unique qualities they bring to our business and we seek to build their expertise and support their individual ambitions at every step. Of course, we take our work seriously and we know our team can operate under great pressure. We work hard and thrive on achievement, but we also know how to have fun and relax too. We regularly host a range of team building days to strengthen our team's connection with each other and reflect on their successes.
Providing employees with a healthy work-life balance is very important to our culture. We have a wide range of employee benefits and we host regular social activities and wellbeing initiatives. We are also committed to supporting our employee's involvement in their communities, by actively fundraising, hosting charity events, and overseeing volunteering opportunities.
Benefits (Only for Permanent and Fixed Term Employees)
Leave
25 days of annual leave with option to buy/sell more days
Adoption and fertility leave
Generous enhanced parental leave
Healthcare
Comprehensive private insurance coverage for employee and dependents
Group Life Insurance coverage of 9x basic annual salary and Group Income Protection up to 75% of basic annual salary
Optical benefits
Savings & Retirement
15% combined employee/employer contributions
Wellness
Subsidized gym membership
Access to Employee Assistance Program
Cycle to Work and Electric Car Salary Sacrifice Scheme
Time off for volunteering
