Senior Applied AI Engineer at Turaco
Turaco View all jobs
- Kenya
- Permanent
- Full-time
- Design, develop, and deploy AI/ML solutions that address real operational and customer-facing problems - from NLP and predictive models to LLM-powered workflows and intelligent automation.
- Translate business requirements into well-scoped AI projects with clear success metrics, timelines, and tradeoffs.
- Own the full ML lifecycle: data exploration, model development, evaluation, deployment, and monitoring.
- Build and maintain robust data pipelines and infrastructure to support model training and inference at scale.
- Lead and mentor a team of engineers, fostering growth through code reviews, pair programming, and knowledge-sharing.
- Collaborate with operations and product teams to embed AI capabilities directly into workflows and products.
- Evaluate and integrate third-party AI tools, APIs, and foundation models (e.g. LLMs) where they offer clear value.
- Create clear technical documentation for both technical and non-technical audiences.
- Proactively monitor deployed models for drift, degradation, and bias, and implement corrective measures.
- Lives Turaco’s values – pushing boundaries, working with excellence, and a profound respect for the individual.
- 7+ years of professional software experience, with at least 3 years in applied AI/ML roles in production environments.
- Startup or entrepreneurial experience is highly desirable – you are comfortable with ambiguity and moving fast.
- Demonstrated strong programming skills in at least two of these languages: Java, Python, Go, or JavaScript; experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Hands-on experience with LLMs and generative AI – prompt engineering, fine-tuning, Reinforcement Learning (RL), RAG architectures, or building LLM-powered applications.
- Solid understanding of classical ML: supervised/unsupervised learning, model evaluation, and feature engineering.
- Experience with data infrastructure – SQL/NoSQL databases, data pipelines, and cloud platforms (AWS, GCP, or Azure).
- Familiarity with MLOps practices: experiment tracking, model versioning, CI/CD for ML, and monitoring in production.
- Strong communication skills, able to translate complex AI concepts clearly for non-technical stakeholders.
- Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or a related field; strong academic track record preferred.
- A creative, first-principles thinker who can identify where AI creates genuine value – and where it doesn’t.
- Excellent team player with strong organizational and leadership skills
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