Do you want to do work that matters? Do you want to help improve the lives of some of the most hardworking people in Africa, while also reducing carbon emissions? Do you want to use your skills to advance Africa and the Global South towards a zero-carbon future, not just to make a living? Ampersand is your answer.

About Ampersand

Ampersand is Africa’s emobility pioneer. Ampersand provides electric motorcycles and charging infrastructure (battery swap stations), uniquely tailored to serve half of Africa’s road fleet: Commercial motorcycle taxi and delivery drivers. Moto taxis are a primary means of public transport in African cities, and it is estimated that these drivers spend >$6Bn p.a. on gasoline in East Africa alone. Ampersand has developed an electric solution that is more powerful, fun to drive, and cost-effective than the incumbent. Ampersand drivers routinely earn over 45% more income by going electric.

The company started in Kigali, Rwanda, and expanded into Nairobi, Kenya in 2022. Today it has around 5,000 e-motorcycles on the road and 58 battery swap stations across the two countries. Ampersand is leading the market in quality, affordable tech, customer traction, and operational systems. The Ampersand team consists of 500+ staff drawn from diverse backgrounds and is working hard to see all 5 million taxi motorbikes in East Africa become electric by 2030. Ampersand is rapidly scaling its operations and is looking for innovative professionals who are passionate about clean energy and environmental impact to lead and contribute to our rapid growth.

Ampersand values innovation, creativity, and continuous improvement. It seeks people who are proactive problem solvers to drive results. Ampersand promotes leadership within the organization and is a place where you can grow your career as you work with some of the brightest and most hard-working individuals in East Africa.

Our Values

• Customer-centric Everyday: We prioritize our customers daily, tailoring solutions to exceed expectations.
• Challenge The Status Quo Through Innovation: Our dedicated teams constantly challenge the status quo, driving innovation to enhance customer experiences and deliver solutions that go beyond expectations
• Love Solving Problems Together: Internal collaboration is our approach; we thrive on solving challenges alongside our customers.
• Stay Agile: We stay agile to swiftly meet dynamic customer needs and adapt to a changing landscape.
• Driven By People And Planet: Beyond business, we're committed to people and the planet, ensuring a positive impact.

About the role

Summary of Duties and Tasks

Model Development:

Design, build, and train machine learning models for a variety of tasks such as prediction, classification, clustering, recommendation, or optimization. Select appropriate algorithms based on problem requirements and data characteristics.

Data Preparation:

Collect, clean, preprocess, and organize large datasets for training and evaluation. Implement feature engineering techniques to enhance model performance and reliability.

Model Evaluation and Validation:

Evaluate models using standard performance metrics and ensure models generalize well to unseen data. Perform cross-validation and robustness testing to identify and fix issues such as overfitting or bias.

Deployment and Maintenance:

Deploy machine learning models into production environments, ensuring they are efficient, scalable, and robust. Monitor model performance post-deployment and retrain or fine-tune models as needed to maintain effectiveness over time.

Technical Troubleshooting:

Diagnose and resolve issues that arise in model training, deployment, or serving. Analyze data and model outputs to troubleshoot unexpected behaviors and implement corrective solutions.

Collaboration:

Work closely with data engineers, software developers, product managers, and other stakeholders to align machine learning solutions with business needs. Communicate findings and model insights clearly to both technical and non-technical audiences.

Continuous Improvement:

Stay updated with the latest research and advancements in machine learning and AI. Propose and implement innovative techniques or tools to improve existing pipelines, model accuracy, and system performance.

Qualifications:

• Strong knowledge of machine learning algorithms, deep learning architectures, and statistical modeling techniques.
• Proficiency in programming languages such as Python (preferred) or C++, Java.
• Experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or similar.
• Familiarity with data preprocessing, feature selection, and model validation techniques.
• Strong problem-solving and analytical skills with attention to detail.
• Ability to explain complex technical concepts to a non-technical audience.
• Experience working with cloud platforms (AWS, GCP, Azure) is a plus.
• Excellent teamwork and communication skills.
• Commitment to following ethical AI practices and ensuring data privacy and security.

Timing

ASAP

Compensation

Compensation commensurates with experience