About the job

Alma is seeking an experienced and visionary Lead Machine Learning Engineer to head our AI/ML team within the Data department. As we expand our ML capabilities across the organisation, we are looking for a dynamic leader to drive innovation, mentor team members, and shape the future of our ML initiatives.

As the Lead Machine Learning Engineer at Alma, you will oversee a team that has successfully developed critical ML solutions for our core business, including risk assessment tools, customer scoring models, and fraud prevention systems. While these risk-related topics remain our priority, you will also lead the charge in expanding our ML capabilities to new and exciting areas of the business.

About the key missions

1) People Management

• Oversee a team of 1 MLOps Specialist and 3 ML Engineers
• Set and track quarterly objectives for team members
• Manage HR matters, including performance reviews and career development
• Conduct regular one-on-ones to ensure team alignment and individual growth

2) Strategic Leadership

• Shape the ML roadmap in alignment with Alma's business goals
• Stay updated on industry best practices and emerging technologies in ML and AI
• Provide technical guidance on key initiatives across the organisation
• Collaborate with other department Heads to identify new opportunities for ML applications
• Drive internal communication to increase visibility and recognition of the ML team's achievements and capabilities across the company
• Contribute to Alma's external presence in the ML community through thought leadership, conference presentations, or technical blog posts, enhancing our reputation as an ML-driven fintech leader

3) Project Management

• Identify and prioritize ML projects based on business impact and technical feasibility
• Assess the technical complexity of proposed projects and allocate resources effectively
• Manage project timelines and deliverables, ensuring high-quality outputs
• Balance resources between maintaining core risk models and exploring new ML initiatives

4) Technical Contribution

• Engage in hands-on work in ML engineering and ML Ops
• Participate in code reviews to maintain high code quality standards
• Mentor team members, fostering a culture of continuous learning and innovation
• Contribute to the architecture and design of complex ML systems

About you

What would make you a good fit for the role:

• Education: Master's degree or Ph. D. in a relevant field (computer science, machine learning, mathematics, engineering, statistics, etc.)
• Experience: 5+ year of full-time permanent experience (internships & apprenticeships excluded) in machine learning, with at least 2 years in a management role
• Strong communication skills, with the ability to explain complex concepts to non-technical and technical stakeholders
• Strong leadership and mentoring abilities
• Language: Fluency in English is mandatory. Fluency in French will be a plus!

Technical qualifications:

• Deep understanding of ML fundamentals, including advanced algorithms and model evaluation techniques
• Strong programming skills in Python and proficiency with ML libraries and frameworks
• Experience with MLOps, cloud platforms (preferably GCP), and containerisation technologies
• Proven track record of successfully delivering ML projects in a production environment

What would make you stand out of the crowd:

• Experience in the Fintech or financial services industry
• Familiarity with risk modelling and fraud detection systems
• Knowledge of natural language processing (NLP) and large language models (LLMs)
• Understanding of data privacy and security best practices

ML Stack: Python, FastAPI, VertexAI, BigQuery, PostgreSQL, Github, scikit-learn

About the recruitment process

• Phone interview with Recruiter (30 mins)
• Technical & Fit assessment interview with MLEs (75 mins)
• Leadership & Behavioural interview with Head of Data (45 mins)
• Final interview with Head of Risk Modelling (30 mins)