Machine Learning Engineer
Twiga Foods
Quick Take
Build, deploy, and monitor machine learning models that power demand forecasting, route optimisation, and price prediction across Twiga Foods' African food distribution network.
At least 3 years of ML engineering experience with strong Python skills and hands-on proficiency in frameworks like TensorFlow, PyTorch, or scikit-learn, plus experience with data pipelines and MLOps.
A competitive above-market salary of KES 160,000–280,000/month, the chance to work on high-impact ML problems at scale, and a front-row seat at one of Africa's most ambitious agri-tech companies.
Job Description
Twiga Foods is on a mission to revolutionise food distribution across Africa by harnessing the power of data and cutting-edge technology. As the company continues to scale its operations, it is looking to bring on board a talented Machine Learning Engineer based in Nairobi to join its growing tech team.
In this role, you will be at the heart of Twiga's data-driven operations, designing and deploying machine learning solutions that directly improve supply chain efficiency. From predicting customer demand to optimising delivery routes, your work will have a measurable impact on how food reaches markets and vendors across the region.
- Design, develop, and deploy machine learning models focused on demand forecasting, route optimisation, and price prediction across Twiga's distribution network
- Handle and process large-scale datasets generated by the company's distribution and logistics operations
- Work closely with software engineers and data analysts to integrate ML solutions into existing systems and workflows
- Continuously monitor the performance of deployed models in production environments, identifying areas for improvement and retraining where necessary
- A minimum of 3 years of hands-on experience working as a Machine Learning Engineer or in a closely related role
- Strong proficiency in Python along with widely used ML frameworks such as scikit-learn, TensorFlow, and PyTorch
- Proven experience building and maintaining data pipelines as well as working within MLOps practices and tooling
- Ability to work collaboratively in a cross-functional team environment involving both technical and non-technical stakeholders
This position is best suited for an experienced machine learning practitioner who thrives in fast-paced, impact-driven environments. If you have a solid engineering foundation, are comfortable working with complex real-world datasets, and are passionate about applying AI to solve practical supply chain challenges in an African context, this could be the ideal next step in your career. Candidates who enjoy seeing their models make a tangible difference in people's daily lives — from smallholder farmers to urban vendors — are especially encouraged to apply.
Interested and qualified candidates should submit their applications through Twiga Foods' official recruitment channels. Ensure your application clearly highlights your relevant machine learning engineering experience, key projects you have worked on, and your familiarity with the tools and frameworks listed above. Only shortlisted candidates will be contacted for further steps in the selection process.
Requirements Breakdown
Must Have
- 3+ years of professional machine learning engineering experience
- Strong Python programming skills
- Hands-on experience with ML frameworks (scikit-learn, TensorFlow, or PyTorch)
- Experience building and maintaining data pipelines
- Familiarity with MLOps practices including model deployment and monitoring in production
Nice to Have
- Experience with supply chain, logistics, or demand forecasting use cases
- Knowledge of cloud platforms (AWS, GCP, or Azure) for ML workloads
- Experience with distributed data processing tools (e.g. Spark, Kafka, or Airflow)
- Familiarity with containerisation and orchestration tools like Docker and Kubernetes
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Salary Context
Above market rate for a Machine Learning Engineer in Nairobi
Machine Learning Engineers in Nairobi typically earn between KES 100,000 and KES 200,000 per month at the mid-senior level, making Twiga's upper range of KES 280,000 notably competitive and reflective of the specialised MLOps and production-deployment skills required. Pay in this field is heavily influenced by years of experience, familiarity with production-grade ML systems, and the ability to work with large-scale real-world datasets.
About Twiga Foods
Twiga Foods is a Nairobi-based B2B food distribution platform that connects smallholder farmers directly to urban food vendors, cutting out inefficient middlemen and reducing post-harvest losses across Africa. Founded in 2014, the company has grown into one of Kenya's most well-funded agri-tech startups, leveraging mobile technology and data to serve thousands of vendors in Nairobi and beyond. Working at Twiga means your code has a tangible impact on food security and the livelihoods of farmers and traders across the continent.
Likely Interview Questions
- 1
Walk us through a machine learning model you built and deployed to production — what was the problem, your approach, and how did you monitor its performance over time?
- 2
How would you design a demand forecasting model for a perishable goods distribution network where data quality and timeliness are inconsistent?
- 3
What does your ideal MLOps pipeline look like, and which tools have you used to build one end-to-end?
- 4
Describe a situation where a model you deployed degraded in production — how did you detect it and what did you do to fix it?
- 5
How would you approach a route optimisation problem across hundreds of daily delivery stops in Nairobi, and what ML or operations research techniques would you consider?
Application Tips
Highlight any end-to-end ML projects where you took a model from experimentation all the way to production monitoring — Twiga needs engineers who can own the full lifecycle, not just build notebooks.
Emphasise experience with time-series forecasting or optimisation problems, as demand forecasting and route optimisation are core to this role and will signal immediate relevance.
Stand out by mentioning any work in resource-constrained or data-noisy environments, such as emerging market or logistics contexts, which closely mirrors the challenges Twiga faces in African food distribution.
Career Path
Roles that lead here
Where this leads
Skills & Keywords
Honest Assessment
Green Flags
- Salary range of KES 160,000–280,000 is transparently disclosed and sits above the typical Nairobi market rate for this seniority level.
- Twiga Foods is one of Africa's most recognised agri-tech companies, offering strong brand credibility and the opportunity to work on ML problems with genuine continental-scale impact.
- The role covers meaningful, real-world ML applications — demand forecasting, route optimisation, and price prediction — rather than internal tooling, meaning your work directly drives business outcomes.
- Cross-functional collaboration with engineers and data analysts suggests a mature data team structure where ML engineers are valued partners rather than isolated contributors.
Watch Out
- The job description does not mention remote or hybrid work options, which may be a concern for candidates seeking flexibility in a post-pandemic work environment.
- Benefits, equity, and non-salary compensation are not mentioned, making it harder to fully evaluate the total package beyond base pay.
- The responsibilities span three distinct ML domains (forecasting, route optimisation, and pricing) which could indicate a broad scope for one engineer without clarity on team size or support structure.
A Day in the Life
A typical week might start with a Monday standup with the data and engineering team to review overnight model performance dashboards and flag any drift in the demand forecasting pipeline. Mid-week could involve iterating on a new route optimisation feature, pulling distribution data from the data warehouse using Python and SQL, running experiments, and syncing with a data analyst who flags unusual patterns from the Nairobi vendor network. By Friday, you might be reviewing a pull request for a newly containerised pricing model heading to staging, writing documentation for the MLOps monitoring setup, and joining a planning session to scope the next quarter's ML roadmap.
Frequently Asked Questions
What qualifications do I need to become a Machine Learning Engineer at Twiga Foods?
You need at least 3 years of ML engineering experience, strong Python skills, and hands-on experience with frameworks like TensorFlow, PyTorch, or scikit-learn, along with practical knowledge of data pipelines and MLOps practices.
Is the Machine Learning Engineer role at Twiga Foods remote or office-based?
The role is listed as based in Nairobi with no mention of remote or hybrid options, so candidates should be prepared for an on-site or Nairobi-based arrangement — it is worth clarifying this during the interview process.
How much does a Machine Learning Engineer earn at Twiga Foods?
Twiga Foods is offering KES 160,000 to KES 280,000 per month for this role, which is above the typical mid-senior ML Engineer salary range in Nairobi, with the final figure likely depending on years of experience and depth of MLOps expertise.
What are the career growth opportunities for a Machine Learning Engineer at Twiga Foods?
Given Twiga's scale and data-driven ambitions across Africa, strong performers could progress into senior or lead ML engineering roles, and potentially into data science leadership positions as the company continues to expand its AI capabilities.
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