Senior Machine Learning Engineer

Zepz; United Kingdom; Remote; GBP 50,000 - 90,000; Full time

Job summary

An innovative firm is seeking a Senior Machine Learning Engineer to join its FinCrime domain. In this role, you will collaborate with cross-functional teams to develop and maintain machine learning processes that enhance fraud detection systems. You'll have the opportunity to shape the technology stack, including Python, Airflow, and Databricks, while mentoring junior engineers. This is a chance to make a significant impact in a remote-first organization that values inclusivity and employee well-being, offering unlimited annual leave and comprehensive medical coverage. If you are passionate about using technology for good and thrive in a collaborative environment, this role is for you.

Benefits

Unlimited Annual Leave

Private Medical Cover

Retirement Plans

Life Assurance

Parental Leave

Cycle-to-work scheme

Employee Discounts

Qualifications

• Extensive experience in designing and productionizing ML systems.
• Solid understanding of ML fundamentals and translating business needs.

Responsibilities

• Build and maintain ML processes for fraud detection systems.
• Collaborate with teams to design and refine work, influencing architectural decisions.

Skills

Machine Learning

Python

SQL

Data Engineering

Statistical Experiment Design

Communication Skills

Education

Bachelor's Degree in Computer Science or related field

Tools

Airflow

Databricks

DynamoDB

Job description

Zepz Group is the group powering leading global remittance brands: WorldRemit and Sendwave. Zepz Group has been disrupting an industry previously dominated by offline legacy players by reducing the barriers to finance and increasing safety and convenience for users. Every day, Zepz Group and its brands work towards unlocking the prosperity of cross-border communities through finance and technology - driven by the vision of a world that celebrates migrants’ impact on prosperity, at home and abroad. Zepz served over 9+ million users through its presence in over 4,600 corridors with over 40 send countries and 90 receive countries.

• We act like owners: We are relentlessly delivering for our users and spending money thoughtfully.
• We embrace embarrassing honesty: We function best when we're open and honest with one another — especially about our challenges and doubts.
• We have a bias to action: We get to first outcomes quickly, iterate and learn.
• We strive to be better: We may make mistakes, but always learn from them.
• We are inclusive: to better reflect and serve our users.

About the role:

We are looking for a Sr Machine Learning Engineer to join our FinCrime domain. This role will report to the Director of Engineering and collaborate with Analytics, Data Science and the wider organisation. Together you will build and maintain ML processes that power our fraud detection systems.

What you will do:

• Help shape what we build. Our current tech stack includes Airflow, Fivetran, DBT, Databricks and DynamoDB and is primarily in Python, leveraging some of the most used machine learning packages. You will build and maintain data pipelines and scalable machine learning inference systems in production.
• Own delivery. We’re driven by shipping value; you’ll own work beyond just a pull request. You’ll care about bugs, scalability, uptime and other non-functional requirements.
• Grow together. You’ll review other’s work and happily seek feedback on yours to ensure we build a better codebase and sharpen each other's skills. We believe in developing our people so you will be an important part of mentoring juniors in the team.
• Collaborate. You’ll be working closely with Product Owners, Data Scientists, Analysts and other Engineers to design and refine our work. We work as a team and your input will be key in many architectural decisions (some that you would own) and in driving consensus.

What you bring to the table:

• You are a software engineer at heart, and you take pride in writing well-designed, robust, and maintainable code to solve problems. We understand code is read more than it’s written, and better off tested. Maintainability is a must.
• Extensive Industrial experience designing and productionising ML systems.
• Solid understanding of Machine Learning fundamentals and ability to translate business requirements into machine learning solutions.
• Experience in statistical experiment design and performance analysis of machine learning models.
• Strong experience with Python, SQL and machine learning frameworks. Some data engineering experience is preferred (Databricks and Airflow are some of the platforms we use, but any equivalent experience is appreciated).
• Excellent communication and presentation skills, with the ability to convey complex concepts to technical and non-technical stakeholders.
• Bias for action. You see a problem, you fix a problem. You get buy-in for your solutions and keep tickets moving. We’re always looking for ways to ship at pace.
• Opinionated. We want you to actively contribute to discussions and help build a shared understanding within the team and organisation.

What you’ll get from us:

Please note that the benefits below will apply to permanent roles.

We have five core benefits for our talent in the US, UK, Philippines, Poland, and South Africa specifically:

• Unlimited Annual Leave: Feel free to make the most of your time off and maintain a healthy work-life balance!
• Private Medical Cover: You can opt-in to a Private Medical Insurance scheme. This provides you with access to thorough medical coverage, so you can feel confident in your health and well-being.
• Retirement: We offer pension schemes to help you plan for and secure your future.
• Life Assurance: Life assurance is available to give you peace of mind and protect your loved ones in case of the unexpected.
• Parental Leave: We offer competitive parental leave schemes to ensure you are spending as much quality time with your new bundle of joy as possible.

We are also remote-first as an organisation, offering flexibility for you to work where you need to be most productive. In addition to the above, you will discover that we have a range of secondary perks (such as the cycle-to-work scheme and employee discounts) depending on your location, to help you thrive at Zepz!

Why choose Zepz?

• Our team of over 1,000 employees is fully distributed across the world. We are working from coffee shops, homes, and co-working spaces — making us one of the larger fully distributed growth-stage startups in the world but we also offer workspace in our talent cluster locations - spaces we can meet, collaborate and connect.
• We are proud parents, community organizers, farmers, band members, yoga teachers, YouTube influencers, former Olympians, and serial entrepreneurs.
• We collectively speak over twenty languages, including Akuapem, Amharic, Bengali, Ewe, Fante, Ga, Igbo, Kalenjin, Luganda, Oromo, Somali, Swahili, Wolof, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hungarian, Irish, Italian, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish and Swedish.
• At Zepz, embodying our commitments binds us together. We are collectively passionate about striving to achieve our vision and purpose - to continue to provide the best service to our users.

Ready to Apply?

Applications will be reviewed on a rolling basis. If interested, please submit your resume along with a cover letter (optional), highlighting why your experience demonstrates you meet the requirements of the role. Please also indicate the countries in which you have work authorization.

Confidence can sometimes hold us back from applying for a job. But we'll let you in on a secret: there's no such thing as a 'perfect' candidate. Zepz is a place where everyone can thrive.

So however you identify and whatever background you bring with you, and if at all you might need any form of support to make the process as comfortable as possible, please let us know and give us a shot by applying. We want you to be excited to wake up to make an impact every day.