Engineering Manager, MLOps

Who we are 

Tractable is an Artificial Intelligence company bringing the speed and insight of Applied AI to visual assessment. Trained on millions of data points, our AI-powered solutions connect everyone involved in insurance, repairs, and sales of homes and cars – helping people work faster and smarter, while reducing friction and waste.

Founded in 2014, Tractable is now the AI tool of choice for world-leading insurance and automotive companies. Our solutions unlock the potential of Applied AI to transform the whole recovery ecosystem, from assessing damage and accelerating claims and repairs to recycling parts. They help make response to recovery up to ten times faster – even after full-scale disasters like floods and hurricanes. 

Tractable has a world-class culture, backed up by our team, who have rated us 4.9/5 on Glassdoor, making us a global employer of choice!

We're a diverse team, uniting individuals of over 40 different nationalities and from varied backgrounds, with machine learning researchers and motor engineers collaborating together on a daily basis. We empower each team member to have tangible impact and grow their own scope by intentionally building a culture centred around collaboration, transparency, autonomy and continuous learning.

What you will do

The MLOps team belongs to a larger group - Platform Engineering, which is focused on building tools and services for our internal customers within Tractable: AI researchers, data scientists, product engineers, operations specialists, etc. We have several teams in the Platforms group tackling different aspects of the space including Infrastructure, Business Intelligence, Data Platform, Dev tools and engineering efficiency, MLOps. As an Engineering Manager on the MLOps team, you will be collaborating with the fellow Platform teams. 

We are looking for an experienced Engineering Manager to build and support a team of extremely talented MLOps engineers. This team enables the core mission of Tractable - to make applied AI possible - by optimising the end-to-end Machine Learning life cycle. The goal of the MLOps team is to enable researchers to spend 80%+ of their time solving tricky ML problems rather than dealing with engineering/infra/ops challenges. 

You'll play a key role in developing our MLOps platform from pretty much ground up. You will influence the scope and technical direction as well as champion best practices within the team. You have a relentless focus on user experience (Researchers and Data Scientists in this case) and you care deeply about what your team is building to make sure it will have the biggest impact on your users. You will be a strong mentor, nurturing an encouraging and supportive environment to enable the team to do their best work.

You will be:

• Playing a pivotal role in building and shaping the vision of our machine learning platform and infrastructure
• Growing and scaling a team of best-in-class Machine Learning Engineers 
• Introducing and driving best practices into the team
• Helping your team define the technical architecture of the machine learning platform
• Managing a team of Engineers and being responsible for their career growth and execution of the roadmap
• Mentoring more junior members of the team and provide technical guidance
• Reviewing design and architecture proposals on your team, giving feedback and advising on best practices.

You are an ideal candidate if you are interested in a leadership role because it allows you to work closely with others to help them achieve their best. Ideally, you have led teams of more than three people and are looking for an opportunity to take on more responsibility and lead a larger team

What you need to be successful:

• 2+ years of experience in supporting teams building and maintaining scalable Machine Learning Platforms. We don’t expect you to write code in this role but in order to be successful, prior hands-on experience with Data/ML engineering is key. Bonus if you have trained a few deep learning models! 
• You’ve seen several examples of various ML Platforms over the course of your career, you know what a successful ML Platform looks like, what works in production, where typical pitfalls are; you’re familiar with the AI infrastructure landscape and what vendors are out there, so you can make an informed build vs. buy decision.
• Exceptional communication skills and collaborative mindset. You will be working closely with your customers - researchers and data scientists - and making sure the tools your team is building are user friendly and tackle the unmet needs of your customers.
• Have empathy towards your customers and product sense. As a manager in the Platforms group, you are excited about wearing the PM hat and think about ML Platform as a product. You enjoy working alongside other managers to craft a shared vision and roadmap for your team.
• The ability to plan and track timelines for your team, ensuring efficient execution and communicating to relevant partners when things change.
• Be able to have technical conversations with your team about the design/system architecture and help your team think through trade-offs (distributed system experience is a plus!). Ability to advocate for best practices in the engineering/MLOps space.
• Be able to  build a high performing team with emphasis on team health and psychological safety.
• Have experience with building hiring processes for your team, ability to work closely with your talent acquisition/people ops partners to attract and retain amazing talent from a diverse set of backgrounds

We rely heavily on the following tools and technologies below – but we are likely to explore new technologies / frameworks as we are building the platform from ground up hence you don't need to have prior experience in all of them. We’re just keen to know that you're willing to break things, fix things, learn fast and carry on building a great team that is capable of building awesome platforms customers love! 

• Main Infrastructure: AWS (EC2, S3, MSK, Lambda, StepFunctions, Glue, IAM, Cognito, Systems Manager, CloudWatch, SQS, Route 53, Sagemaker), Apache Kafka (AWS MSK), Kubernetes, Datadog (Metrics, Logs, Synthetics), Pagerduty
• Main CI/CD: Terraform, Docker, Harness
• Main Databases: Postgres / RDS, Redis, DynamoDB
• Main Languages: Python, Node + Typescript
• Main ML stack: Triton, TFServing, KServe

We encourage you to drop us a line even if you don’t have all the points above. That’s a lot of different areas of responsibility! We will help you pick them up because we believe that great people come from all walks of life.

What’s in it for you

• Competitive salary
• 6 month salary reviews
• Visa sponsorship (if required)
• Equity
• Pension scheme
• Bupa private healthcare (full coverage)
• Flexible hours & WFH/hybrid setups 
• Learning and Development budget
• Competitive maternity + paternity leave
• Daily office snacks & soft drinks 
• Regular company office events such as Games Nights, Movie Nights, Lunch & Learns, Monthly Brunch and more

Diversity commitment

At Tractable, we are committed to building a diverse team and inclusive workplace where people’s varied backgrounds and experiences are valued and recognised. 

We encourage applications from candidates of all backgrounds and offer equal opportunities without discrimination.

#LI-HM1

Diversity commitment

At Tractable, we are committed to building a diverse team and inclusive workplace where people’s varied backgrounds and experiences are valued and recognised. 

We encourage applications from candidates of all backgrounds and offer equal opportunities without discrimination.