1,003 AI Governance jobs in Kenya

• Fundamentals of data science, statistics, and machine learning concepts.
• Data manipulation and analysis using Python and SQL.
• Building and evaluating machine learning models (classification, regression, clustering).
• Introduction to deep learning and neural networks.
• Data visualization techniques to communicate findings.
• Best practices for data preprocessing and feature engineering.
• Working effectively in a remote, collaborative team environment.

• A keen interest in data science, AI, and machine learning.
• Strong logical reasoning and problem-solving abilities.
• Basic understanding of mathematics and statistics.
• Familiarity with programming concepts is a plus.
• Excellent communication skills and a proactive learning attitude.
• Ability to work independently and manage time effectively in a remote setting.
• Must be eligible to work remotely within Kenya.

• Designing end-to-end AI and machine learning solutions to address complex business challenges.
• Architecting scalable and robust ML pipelines for data processing, model training, and deployment.
• Leading the development and implementation of predictive models, NLP systems, and computer vision applications.
• Evaluating and selecting appropriate AI technologies, frameworks, and cloud services.
• Collaborating with data scientists and engineers to ensure efficient and effective solution delivery.
• Providing technical leadership and guidance to AI/ML teams.
• Communicating complex technical concepts to non-technical stakeholders.
• Staying current with the latest research and advancements in AI and machine learning.

• Minimum of 8 years of experience in AI, machine learning, or data science, with 3+ years in an architect or lead role.
• M.Sc. or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field; M.Sc. required.
• Extensive experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Expertise in Python or R, and deep learning frameworks (TensorFlow, PyTorch).
• Proven ability to design and deploy production-level AI solutions.
• Strong understanding of various machine learning algorithms and data science methodologies.
• Excellent leadership, communication, and problem-solving skills.
• Ability to thrive in a dynamic, remote work environment.

• Develop and implement comprehensive AI ethics principles and guidelines.
• Conduct thorough ethical risk assessments and bias audits for AI/ML models.
• Design and oversee fairness, accountability, and transparency (FAT) initiatives for AI systems.
• Advise engineering and product teams on ethical considerations throughout the AI development lifecycle.
• Stay current with global AI regulations, standards, and best practices.
• Collaborate with legal and policy teams to ensure compliance and shape ethical AI strategies.
• Develop training materials and conduct workshops on AI ethics for internal stakeholders.
• Engage with external stakeholders, researchers, and policymakers on AI ethics issues.
• Promote a culture of responsible AI innovation within the organization.
• Contribute to public discourse and thought leadership on AI ethics.

• Advanced degree (Master's or Ph.D.) in Ethics, Philosophy, Law, Computer Science, Data Science, or a related field with a focus on AI ethics.
• Proven experience in developing and implementing AI ethics frameworks or policies.
• Strong understanding of machine learning concepts and their ethical implications.
• Familiarity with fairness, accountability, and transparency (FAT) techniques in AI.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional written and verbal communication and presentation abilities.
• Demonstrated ability to work independently and collaboratively in a remote setting.
• Experience in a technology or research-intensive environment is a plus.

• Data Preprocessing and Exploration
• Feature Engineering and Selection
• Supervised and Unsupervised Machine Learning Algorithms (e.g., Regression, Classification, Clustering)
• Model Evaluation and Tuning
• Introduction to Deep Learning Concepts
• Data Visualization and Storytelling
• Programming with Python (libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
• Big Data Technologies (exposure to platforms like Spark)
• Version Control (Git) and Collaboration Tools
• Best practices for remote collaboration and communication in a tech environment.

• Strong analytical and quantitative skills.
• Proficiency in at least one programming language, preferably Python.
• Understanding of basic statistics and calculus.
• A keen interest in data science, machine learning, and artificial intelligence.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and manage time effectively in a remote setting.
• Good communication skills, with the ability to explain technical concepts to a non-technical audience.
• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience.
• Must be eligible to work remotely from Kenya.

• Assist in collecting, cleaning, and transforming large datasets.
• Perform feature engineering and data preprocessing for machine learning models.
• Implement and test various machine learning algorithms.
• Support the evaluation and validation of model performance.
• Collaborate with senior data scientists on ongoing research projects.
• Document code, methodologies, and findings.
• Assist in preparing data visualizations and reports.
• Contribute to team discussions and brainstorming sessions.

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Solid understanding of statistical concepts and machine learning principles.
• Proficiency in Python or R programming.
• Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with data manipulation libraries (e.g., Pandas) and SQL.
• Strong analytical and problem-solving skills.
• Eagerness to learn and adapt in a research-focused environment.
• Good communication and teamwork abilities.

Company Description
At
Timu AI
, we believe every business deserves a smarter teammate.

We're building
AI-powered infrastructures
that save time, cut costs, and help companies focus on what matters — their clients and their growth.

Role Description
This is a full-time role for a Machine Learning Engineer and AI specialist at The role is Remote. The Machine Learning Engineer will be responsible for developing and implementing machine learning models and algorithms, As an
AI Automation Engineer
, you'll design, build, and scale automation workflows that connect business tools, integrate AI intelligence, and create seamless digital teammates for our clients.

You'll collaborate directly with the founder and help shape the future of automation infrastructure in Africa

Key Responsibilities

• Build and optimize
  n8n workflows
  for real-world business use cases (starting with the Legal Industry).
• Connect APIs (Google Calendar, WhatsApp Business API, CRMs, Gmail, etc.).
• Integrate
  AI features
  using OpenAI API or LangChain (for scheduling, smart responses, or data analysis).
• Manage workflow hosting and deployment (self-hosted or cloud environments).
• Implement authentication, error handling, and logging within workflows.
• Collaborate in developing a repeatable
  automation framework
  for future industries.
• Write documentation for all automations built.

Qualifications

• Hands-on experience with
  n8n
  ,
  Make (Integromat)
  , or
  Zapier
  .
• Strong understanding of
  APIs
  ,
  webhooks
  , and
  JSON
  .
• Proficient in
  JavaScript/TypeScript
  or
  Python
  .
• Experience with
  databases
  (Airtable, PostgreSQL, or MongoDB).
• Familiarity with
  AI tools/APIs
  (OpenAI, HuggingFace, LangChain).
• Understanding of basic
  data security and authentication
  practices.
• Strong problem-solving mindset and willingness to learn fast.

What You'll Gain

• Equity in Timu AI — you'll own part of what we build.
• A real seat at the table as one of the founding engineers.
• A chance to shape how AI automation is implemented across multiple industries.

If you've ever wanted to be
part of something from day one
— this is it.

We're not hiring an employee.

We're bringing in a
partner
who believes in Africa's potential to build world-class AI systems.

How to Apply
Send your portfolio or project samples (GitHub, Notion, or screenshots) + a short note explaining:

"How would you automate appointment scheduling for a firm?"
Email :

Subject Line:
AI Automation Engineer – (Your Name)

• Gain practical experience in Python, R, SQL, and relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Learn to clean, transform, and analyze large datasets to extract meaningful insights.
• Develop and implement machine learning models for various applications, such as classification, regression, and clustering.
• Understand the principles of deep learning and neural networks.
• Participate in code reviews and collaborate with senior team members on project development.
• Contribute to data visualization and reporting efforts to communicate findings effectively.
• Receive dedicated mentorship and training on advanced data science and ML concepts.
• Develop proficiency in cloud platforms (e.g., AWS, Azure, GCP) for data storage and model deployment.
• Engage in continuous learning and exploration of new tools and techniques in the AI landscape.
• Work on challenging projects that directly impact business strategies and product development.

• Design, develop, and implement state-of-the-art machine learning models and algorithms.
• Lead the end-to-end ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Architect scalable and robust ML systems for production environments.
• Conduct research on new ML techniques and technologies to identify opportunities for innovation.
• Mentor and guide junior ML engineers, fostering technical growth and best practices.
• Collaborate with data scientists, software engineers, and product managers to define ML requirements and deliverables.
• Optimize ML models for performance, accuracy, and efficiency.
• Develop and implement strategies for monitoring and maintaining ML models in production.
• Stay abreast of the latest advancements in AI and machine learning research and industry trends.
• Communicate complex technical concepts and project updates to both technical and non-technical stakeholders.

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 8-10 years of experience in machine learning engineering or related roles, with a strong track record of delivering impactful ML solutions.
• Extensive experience with various ML algorithms (e.g., deep learning, reinforcement learning, supervised/unsupervised learning).
• Proficiency in programming languages such as Python, Java, or C++.
• Strong experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
• Excellent understanding of data structures, algorithms, and software design principles.
• Strong analytical and problem-solving skills.
• Proven ability to lead technical projects and mentor team members.
• Exceptional communication and collaboration skills, with the ability to thrive in a remote setting.

• Conduct state-of-the-art research in deep learning for computer vision, including object detection, image segmentation, facial recognition, and generative models.
• Develop and implement novel AI algorithms and models, optimizing for performance and accuracy.
• Design and execute rigorous experiments to validate research hypotheses.
• Collaborate with cross-functional teams to integrate research prototypes into product development.
• Publish research findings in leading academic journals and present at international conferences.
• Mentor junior researchers and engineers, fostering a collaborative research environment.
• Stay abreast of the latest advancements and trends in AI, machine learning, and computer vision.
• Contribute to the intellectual property portfolio through patent applications.
• Lead research initiatives and define research roadmaps in specific areas of computer vision.
• Explore new application domains for computer vision technologies.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
• Minimum of 7 years of post-doctoral research experience in AI, with a specialization in Deep Learning and Computer Vision.
• A strong publication record in top-tier AI conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML).
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Proficiency in programming languages like Python and experience with scientific computing libraries.
• Deep understanding of various neural network architectures (CNNs, RNNs, Transformers) and their applications.
• Experience with large-scale datasets and distributed training.
• Excellent analytical, problem-solving, and critical thinking skills.
• Proven ability to lead research projects and work effectively in a remote, collaborative setting.
• Strong communication and presentation skills.