Software Engineer (Machine Learning)

In brief

**Overview** This role is for a Software Engineer (Machine Learning) within SFTx, a newly established digital-first business unit of the Sanlam Group. SFTx aims to democratize financial advice and solutions across Africa, pioneering inclusive financial confidence and helping people build generational wealth. The unit fosters a culture of agility, constant deployment, and rapid, cost-effective learning, striving to create an environment where knowledge workers can accelerate ideas, bring innovation to market, and realize their career aspirations. The Software Engineer ML is an independent contributor responsible for owning ML-driven and data-intensive features from concept to production. This includes mentoring junior engineers and actively improving team practices. The position requires the ability to work autonomously, solve problems across the codebase and data/ML stack, and collaborate effectively with cross-functional teams. This individual will deliver complete features and models independently, demonstrating growing influence beyond individual tasks to impact the broader team. Reporting to a Tech Lead, the role demands solid technical expertise, a proven ability to deliver end-to-end solutions across data and ML systems, and emerging leadership skills in mentoring and process improvement. The successful candidate will work closely with Product Management and Design teams to understand business context, collaborate with engineering peers, and actively participate in improving development, testing, and operational practices. **What you will do** * **Feature Ownership & Delivery:** Take full ownership of new features and ML/data products, delivering them from concept to production independently, without constant direction. Design and implement moderately complex systems, including ML pipelines and data workflows, understanding trade-offs. Solve problems across the codebase, data, and ML components, balancing feature delivery with long-term code quality, and proactively addressing technical debt. * **Code Quality & Technical Excellence:** Focus on operational and code excellence in reviews and development. Contribute to coding standards, ensure code efficiency and reusability, and write robust, well-tested code. Actively participate in code reviews, provide constructive feedback, apply design principles and best practices, and work with multiple frameworks and libraries, including ML frameworks like scikit-learn, TensorFlow, or PyTorch. * **ML Engineering:** Apply understanding of the ML model lifecycle (training, evaluation, deployment, monitoring). Design and maintain data pipeline orchestration and workflow management, apply data versioning, feature stores, and ML metadata management. Build and maintain model serving patterns and APIs for ML systems, and articulate pros and cons of relevant data structures and algorithms for time and space complexity. * **Operational Excellence:** Actively participate in on-call rotations and handle incidents effectively. Implement robust monitoring, logging, and alerting for owned features, services, and ML systems. Respond promptly to production issues, escalate appropriately, contribute to incident postmortems, and apply operational practices (scalability, robustness, fault tolerance, load balancing, health checking) to ensure system and model reliability. * **Cross-functional Collaboration:** Work effectively with Product Management and Design teams to understand business context and requirements, and shape solutions. Collaborate effectively with engineering team members, communicate complex technical ideas clearly, facilitate team discussions, and contribute to team decision-making. * **Team Improvement & Mentorship:** Proactively improve the team's development, testing, and operational practices. Begin mentoring junior engineers and provide constructive feedback. Take ownership of tasks and demonstrate leadership in feature delivery, demonstrating growing influence beyond individual tasks and guiding team members. **Requirements (from the original advert)** * Relevant degree or diploma in Computer Science, IT, or related field or equivalent practical experience. * Typically 5+ years of software engineering experience. * Proficient in multiple programming languages with understanding of language-specific best practices. * Comfortable with complex algorithms and optimised data structures. * Experience with distributed systems, APIs, databases, and scalable architecture. * Understanding of cloud-based infrastructure and operational practices (monitoring, metrics, fault tolerance). * Exposure to ML frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. * Ability to work autonomously, solve problems across the codebase and data/ML stack, and collaborate effectively with cross-functional teams. * Solid technical expertise, proven ability to deliver end-to-end solutions across data and ML systems, and emerging leadership skills in mentoring and process improvement. * *Preferred (but not a prerequisite):* Knowledge of cloud services such as AWS VPC, Auto Scaling, serverless computing, storage EBS, S3, containers, and DNS. **Who should apply** The ideal candidate is an individual with: * **Independent Contribution:** A proven ability to work independently on moderately complex problems, make sound technical decisions, and deliver complete features and ML/data solutions without constant supervision. * **Problem-solving Skills:** Efficiency in debugging and troubleshooting moderately complex issues across code and data/ML systems, with the ability to analyse problems systematically and develop effective solutions with minimal guidance. * **Collaboration & Communication:** Strong communication skills to facilitate team discussions, work effectively across functions, explain technical concepts clearly, and build positive working relationships with Product, Design, and Engineering colleagues. * **Business Awareness:** An understanding of business context and how technical and ML work supports product goals, with awareness of the business model and the ability to contribute to product decisions from a technical perspective. * **Mentorship Capability:** An individual who is beginning to develop coaching skills through mentoring junior engineers, providing constructive feedback, and helping others grow their capabilities. * **Required Behavioural Competencies (SFTx's 6 Leadership Principles):** * **Ownership Mindset:** Accountable for actions and decisions, learning and growing from experiences. * **Growth Mindset:** Always learning and improving, embracing challenges and failures as opportunities. * **Customer Centricity:** A deep understanding of the customer, led by their feedback and behaviours. * **Innovation Jugaad:** Applying creativity to turn obstacles into opportunities, doing more with less. * **Velocity:** Moving fast and working iteratively to deliver customer value without sacrificing long-term value. * **Inclusion:** Seeking out and valuing different perspectives. **Deadline** Not specified **Reference** Original posting: https://www.myjobmag.co.za/job/software-engineer-machine-learning-sanlam-1 Source: myjobmag

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At a glance

• At least 5 years of experience.

• AWS

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