Lead Machine Learning Engineer
2 weeks ago
About Builder.ai
We’re on a mission to make app building so easy everyone can do it – regardless of their background, tech knowledge or budget. We’ve already helped thousands of entrepreneurs, small businesses and global brands, like NBC Universal and Pepsi, as well as American organizations like Bobcat and Smart Path, achieve their software goals. And we’ve only just started
Builder.ai was voted as one of 2023’s ‘Most Innovative Companies in AI’ by Fast Company, and won Europas 2022 ‘Scaleup of the Year’. Our team has grown to over 800 people across the world and our recent announcement of $250m Series D funding (and partnership with Microsoft) means there’s never been a more exciting time to become a Builder.
Life at Builder.ai
At Builder.ai we encourage you to experiment Each role at Builder has unlimited opportunities to learn, progress and challenge the status quo. We want you to help us become even better at supporting our customers and take AI app building to new heights.
Our global team is diverse, collaborative and exceptionally talented. We hire people for their differences but all unite with our shared belief in Builder’s HEARTT values: (Heart, Entrepreneurship, Accountability, Respect, Trust and Transparency) and a let’s-get-stuff-done attitude.
In return for your skills and commitment, we offer range of great perks, from hybrid working and a variable annual bonus, to employee stock options, generous paid leave, and trips abroad #WhatWillYouBuild
Why We Need This Role
We are looking for a Technical Lead profile to manage the MLOps unit within the Intelligent Systems Group. The unit is currently horizontal, it includes both Platform and Machine Learning engineers and it is responsible for supporting data scientists in deploying, maintaining and monitoring an increasing number of Python-based microservices, ETL pipelines, SaaS models, databases and vector stores. The MLOps Lead would need to act as an interface between data scientists, the data & analytics team and the platform engineering team.
We need this role to keep upgrading our AI infrastructure to be more resilient and scalable, while we face increasing demands for support on development, deployments, monitoring and maintenance from the Intelligent Systems team. The role is needed to effectively plan and execute the roadmap for the MLOps team accounting for data science and product stakeholders, infrastructure and cost constraints. Support the definition of service architectures for new services while continuously working towards the minimisation of existing technical debt.
The role would also act as an engineering manager and act as a direct point of contact for the team members. Further responsibilities would include the setting and review of quarterly goals for the team, participation in the hiring process for new team members, oversee and monitor team performance during and after probation.
Why You Should Join
The position will be at the intersection of data science and development operations. The candidate would want to join because of the extreme variety of problems we are facing: support to data scientists in the development of AI-based APIs; support the design, implementation, deployment, maintenance of our microservices infrastructure, data and model training pipelines. This is an engaging role and the ideal candidate should be an eager problem solver that takes pride in the production of clean, robust and scalable solutions.
Our Tech Stack
- Python
- SQL
- Cypher
- Git/Gitlab and CI/CD workflows
- Terraform
- Docker and Kubernetes (kubectl, helm, helmfile)
- AWS, Azure
Requirements
Great communication skills, ability to work in a diverse team and the emotional intelligence required to work with human capital are a must. Confident, but realistic, in their own skills and open to learning new approaches and solutions. Strong software engineering experience with Python. Experience working on production-level microservices (Docker/Kubernetes) and cloud infrastructure. Experience working with Databases, Postgres, Redshift, Neo4j would be a plus.
Skills
- Computer Science or Software Engineering degree / BSc or higher
- Experience leading a Machine Learning / MLOps team
- Low ego management style
- Strong Python coding experience
- Experience with the SQL querying language
- Experience working with Docker both in development and deployment environments
- Experience reading/implementing CI/CD workflows
- Experience with software engineering best practices: unit testing (with mocks), code reviews, design documentation, excellent debugging, troubleshooting skills
- Excellent communication & drive to learn and experiment
- Passionate about loosely held values and ideas. We want someone who has experience but is not blinded by the path already taken.
- Makes decisions based on data and evidence.
Added bonus
- Background in running Kubernetes
- Experience with Graph databases
- Hands-on experience in all facets of automation and systems architecture, with particular focus on Linux and open source technologies
- Experience with GitLab
- Experience working in Cloud environments, in particular Azure or AWS
Benefits
- Attractive quarterly OKR bonus plan or commission scheme dependant on your role
- Stock options in a $450 million funded Series D scale-up company
- 24 days annual leave + bank holidays
- 2 x Builder family days each year
- Time off between Christmas and New Year
- Generous Referral Bonus scheme
- Pension contributions
- Private Medical Insurance provided by AXA
- Private Dental Insurance provided by Bupa
- Access to our Perkbox
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