Principal ML Ops Engineer

At Quantexa we believe that people and organizations make better decisions when those decisions are put in context – we call this Contextual Decision Intelligence. Contextual Decision Intelligence is the new approach to data analysis that shows the relationships between people, places and organizations - all in one place - so you gain the context you need to make more accurate decisions, faster. 

Founded in 2016 Quantexa helps organizations make their data more meaningful, and is the world’s leading software company providing a single networked view of internal and external data as an input to human and AI driven decision making. From compliance, fraud, anti-money laundering and credit risk to customer intelligence and master data management, Quantexa partners with Global Tier 1 Insurers and Banks, Government Agencies, Telecoms and Technology companies to deliver Contextual Decision Intelligence. 

Since being founded we’ve: 

• Grown to 700+ employees 

• Achieved “Unicorn” status being valued at over $1B in 2023 

• Recognised global tech leader by multiple researchers including both Gartner and Forrester 

As part of our ongoing growth we’re standing up an ML Ops team to more efficiently build, maintain and deploy the increasing number of AI models we provide with our platform. We’re recruiting the Team Lead to establish and run this new team. You’ll be supporting our two Data Scientist teams who create the generic Machine Learning Models and Data Science based components for use in our solutions. Our Analytical Innovation Team focuses on structured data, especially graph-based models and detection of risk. Our NLP group teaches machines to understand natural language, building products to help extract meaning and insight from text, while also conducting exploratory research that we believe will drive improvements in our products and advance the state-of-the-art.  

The key objectives for the ML Ops role will be to support both these teams:

• To make it faster, and more predictable for both Quantexa’s in-house Data science teams to build, deploy, monitor and maintain the various types of Machine Learning model we are creating.
• Make deployment of models on site and in cloud simpler, faster and more consistent.
• Where possible, and appropriate, the tools created should be extensible for use by clients for their custom ML models based on Quantexa Platform.

The key objectives for the ML Ops team will be to: 

• To make it faster, and more predictable for both teams to build, deploy, monitor and maintain the various types of Machine Learning model we are creating.  
• Make deployment of models on site and in cloud simpler, faster and more consistent. 
• Enable the tools created to also be used by our clients for their custom ML models based on Quantexa Platform.  

Responsibilities 

• Establish the Quantexa ML Ops team and the team’s interfaces to other parts of Quantexa. 
• Advance our approaches to deployment of ML models within our platform.  
• Work with Architects and DS teams to select appropriate model architectures and patterns, including detailed dependencies. Optimise models to meet non-functional requirements. Document new approaches for reuse.  
• Building tools and processes to stand up required modelling environments on cloud, including environments with specialised capabilities such as GPUs. 
• Compose frameworks to support the Deployment, Testing, Monitoring and Governance of models. 
• Input into selection of 3rd party products and tools, as required, including any Vendor selection 
• Provide support for teams using ML models. Examples include liaising with cloud and DS teams to resolve issues with live models, supporting client deployment of models in partnership with DS teams; Providing Model API support to Quantexa’s platform teams. 

Requirements

What do I need to have? 

• Take pride in designing, productionising and deploying high quality, well-engineered, Machine Learning Training and Inference Pipelines and tools to improve the efficiency of Data Scientists.  
• Experience of Leading a team and mentoring junior engineers. 
• Guiding team members through technical issues and challenges. 
• Ensuring that engineers are following best practices and standards. 
• Leading SCRUM ceremonies and fostering a collaborative and fun working environment that values high performance and continuous improvement. 
• Great MLOps development experience: 
• Write defensive, fault tolerant, efficient and well-engineered code following best software engineering practices.  
• Experience in code profiling and low-level optimization 
• Good knowledge of a range of ML Ops tools such as MlFlow, Kubeflow, DVC or Weights and Biases. 
• Knowledge of the technologies used within the Quantexa platform and especially ML components within it: 
• Container architectures, especially Kubernetes, Docker, and related technologies such as Terraform and Helm 
• Dev and ML Ops  tooling/automation written with Bash, Python, Jenkins and Groovy.  
• Python and the most established ML Libraries such as pytorch and sklearn.  
• Cloud platforms (GCP, Azure, AWS) 
• Fascination with emerging technology and a passion for improving Machine Learning solutions.  

Experience in the following would be beneficial:  

• Hands on experience with Quantexa software or knowledge of the core components of the platform (Spark, Scala, Key-value stores like Elastic Search)  
• Experience with NLP technologies such as sequence-to-sequence models, transformer-based architectures, tokenisation, parsing, and heuristic search algorithms such as beam search. 
• Experience with embeddings, feature stores, and approximate nearest neighbor search. 
• Experience fine-tuning and deploying large language models (LLMs).  
• Experience deploying production grade inference pipelines that use GPUs. 

Benefits

Why join Quantexa?

We know that just having an excellent glass door rating isn’t enough, so we’ve put together a competitive package as a way of saying thank you for all your hard work and dedication.

We offer:

• Competitive salary 💰
• Company bonus
• Private healthcare, Life Insurance & Income Protection
• Cycle Scheme and TechScheme
• Free Calm App Subscription #1 app for meditation, relaxation and sleep 🧘‍♀️
• Pension Scheme with a company contribution of 6% (if you contribute 3%)
• 25 days annual leave (with the option to buy up to 5 days) + birthday off! 🌴
• Ongoing personal development
• Great WeWork Office Space & Company wide socials

Our mission

We have one mission. To help businesses grow. To make data easier. And to make the world a better place. We’re not a start-up. Not anymore. But we’ve not been around that long either. What we are is a collection of bright, passionate minds harnessing complexities and helping our clients and their communities. One culture, made of many. Heading in one direction – the future.

It's all about you

Quantexa is proud to be an Equal Opportunity Employer. We’re dedicated to creating an inclusive and diverse work environment, where everyone feels welcome, valued, and respected. We want to hear from people who are passionate about their work and align with our values. Qualified applications will receive consideration for employment without regard to their race, colour, ancestry, religion, national origin, sex, sexual orientation, gender identity, age, citizenship, marital, disability, or veteran status. Whoever you are, if you’re a curious, caring, and authentic human being who wants to help push the boundaries of what’s possible, we want to hear from you.

Internal pay equity across departments is crucial to our global compensation philosophy. Grade level and salary ranges are determined through interviews and a review of experience, education, training, knowledge, skills, and abilities of the applicant, equity with other team members, and alignment with market data.

Quantexa is committed to providing reasonable accommodations in our talent acquisition processes. If you require support, please inform our Talent Acquisition Team.