1,042 Lead AI Ethics Researcher jobs in Kenya

• Lead research initiatives focused on identifying and mitigating ethical risks associated with AI systems, including bias, fairness, transparency, accountability, and privacy.
• Develop and implement robust ethical guidelines, frameworks, and best practices for AI development and deployment across various applications.
• Collaborate closely with AI engineers, data scientists, product managers, and legal teams to ensure ethical considerations are integrated into the AI lifecycle.
• Conduct comprehensive ethical risk assessments and provide actionable recommendations for AI model design, data governance, and algorithmic decision-making.
• Stay at the cutting edge of AI ethics research, policy developments, and societal implications of artificial intelligence.
• Publish research findings in leading academic journals and present at international conferences.
• Engage with external stakeholders, including policymakers, academics, and civil society organizations, to foster dialogue and advance the field of AI ethics.
• Develop educational materials and training programs to promote ethical AI awareness and practices within the organization.
• Mentor junior researchers and contribute to building a culture of ethical AI development.

• Ph.D. or Master's degree in Computer Science, Philosophy, Law, Ethics, Social Sciences, or a related interdisciplinary field with a specialization in AI ethics.
• Extensive experience (8+ years) in AI ethics research, policy analysis, or responsible AI development.
• Deep understanding of machine learning algorithms, AI systems, and their potential societal impacts.
• Proven ability to conduct rigorous research, publish influential work, and translate complex ethical concepts into practical guidance.
• Strong analytical and critical thinking skills with a nuanced understanding of ethical theories and frameworks.
• Excellent communication, negotiation, and collaboration skills, with the ability to engage diverse audiences.
• Experience in developing AI ethics policies, standards, or regulatory frameworks.
• Familiarity with global AI regulations and compliance requirements.
• A passion for advancing responsible and human-centric AI.

• Develop and implement a comprehensive AI ethics framework, policies, and guidelines for the organization.
• Conduct in-depth research on emerging ethical challenges in AI, including bias, fairness, accountability, privacy, and transparency.
• Analyze AI models and algorithms for potential ethical risks and biases, proposing mitigation strategies.
• Collaborate with AI engineers, data scientists, product managers, and legal teams to integrate ethical considerations into the entire AI development lifecycle.
• Stay abreast of global AI ethics regulations, standards, and best practices, ensuring organizational compliance.
• Lead and mentor a team of AI ethics researchers and specialists.
• Develop and deliver training programs on AI ethics to internal teams.
• Publish research findings, contribute to academic discourse, and represent the organization at relevant conferences.
• Advise senior leadership on strategic ethical considerations related to AI development and deployment.
• Foster a culture of ethical awareness and responsibility throughout the organization.

Job Title: AI Risk & Governance Specialist – AI Stewardship Squad

Location
: Remote from LATAM |
Type
: Full-time Vendor

Company
:

About the Role

As part of Inallmedia's AI Stewardship Squad, you will be responsible for designing and running an end-to-end
AI Risk Management program
that goes beyond checklists. This role is focused on
operationalizing AI responsibility
at scale—helping enterprise teams navigate the complexities of deploying generative and predictive models across sensitive, regulated, or high-impact environments.

You'll work closely with engineering, legal, product, and AppSec to implement frameworks such as
NIST AI RMF 1.0
,
ISO/IEC 42001
, and
ISO/IEC 23894
in real-world settings—balancing risk, usability, and compliance. You'll also prepare organizations to meet emerging global obligations, including the
EU AI Act
and
U.S. privacy regulations
.

If you've led model risk efforts, collaborated across functions, and know how to turn policy into practice, this is your opportunity to build governance structures that scale with AI adoption.

Key Responsibilities

• Maintain an AI System Inventory and Risk Register covering internal and third-party systems (SaaS/LLMs), including key risk domains: bias, robustness, privacy, hallucinations, misuse, drift, and security.
• Execute the full risk lifecycle (identify → assess → treat → monitor) mapped to NIST RMF functions (Map / Measure / Manage / Govern).
• Define and document AI-specific control objectives, mapped to ISO/IEC 42001 clauses (roles, policies, internal audits, continuous improvement), referencing ISO/IEC 23894 for risk processes.
• Lead technical assurance activities: bias/fairness testing, LLM safety evaluations, prompt injection/jailbreak testing, and rollback protocols.
• Align red teaming practices to OWASP Top 10 for LLM Applications; coordinate independent validation of high-risk or regulated models (e.g., under SR 11‑7).
• Embed risk due diligence in vendor onboarding and model acquisition processes; align with CISO (cybersecurity) and Legal/Privacy for PII and cross-border data flow compliance.
• Ensure U.S. privacy obligations are addressed (CCPA/CPRA, Colorado CPA); coordinate readiness for EU AI Act deployer duties including logging, incident handling, and human oversight.
• Run AI risk, ethics, and incident committees; publish dashboards and executive-level reporting (Audit, Risk Committee, BoD).
• Codify usage policies (prompt hygiene, PII, approvals); deliver role-based training to internal teams and promote safe, compliant AI usage across business units.

Ideal Candidate

• 7–10+ years in risk management, governance, or GRC, including 3+ years in AI/ML or model risk.
• Hands-on experience with NIST AI RMF 1.0; working familiarity with ISO/IEC 42001 and ISO/IEC 23894.
• Demonstrated implementation of AI-specific controls: telemetry for drift/performance, bias audits, privacy-by-design, prompt safety evaluation.
• Familiarity with SR 11‑7 / OCC 2011‑12 if coming from financial services or high-risk model environments.
• Proven experience working with U.S.-based companies and engaging with U.S. legal, compliance, and engineering stakeholders.
• Excellent command of English (written and spoken); able to drive cross-functional conversations with clarity and credibility.
• Availability for time zone overlap with U.S. (ET or PT); accustomed to near-shore delivery models and distributed collaboration.

Recommended Stack

Frameworks
: NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894

Red Teaming
: OWASP LLM Top 10, adversarial testing, prompt-injection simulators

Telemetry & Controls
: MLflow, Prometheus, OpenTelemetry, model registries

GRC Tools
: Archer, ServiceNow, internal risk registers

Languages
: Python or SQL (for audit traceability & telemetry queries)

Compliance Contexts
: SR 11‑7, OCC 2011‑12, CCPA/CPRA, EU AI Act (deployer role)

Infrastructure
: Cloud environments with VPN/VPC, RBAC, encryption-at-rest, audit logging

Infrastructure & Environment

• 100% remote across LATAM
• Secure infrastructure: MFA, VPN, RBAC, encrypted storage
• Git-based version control for policies, templates, and evidence documentation
• Integrated with DevOps/ML teams for real-time telemetry and control enforcement
• Cross-collaboration with Legal, Compliance, InfoSec, and Product Governance teams

What We're
Not
Looking For

• Candidates focused solely on legal/policy without experience operationalizing risk controls
• Profiles limited to academic or theoretical frameworks with no deployment exposure
• GRC professionals unfamiliar with AI system behavior, telemetry, or model risk specifics
• Anyone without hands-on experience engaging with U.S.-based organizations

Next Steps

If you're ready to move beyond theory and help
build responsible AI practices at scale
, we'd love to hear from you.

Apply now and help shape the future of
AI governance and risk management
in live production environments.

• 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.

• 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.

• Lead research initiatives in deep learning, computer vision, and related AI fields.
• Develop and implement novel algorithms for image and video understanding, including segmentation, classification, and tracking.
• Design and train complex neural network architectures (CNNs, RNNs, Transformers, etc.) using frameworks like TensorFlow, PyTorch, or JAX.
• Evaluate and optimize model performance, ensuring robustness and scalability for real-world deployment.
• Stay abreast of the latest advancements in AI research and identify opportunities for innovation.
• Collaborate with engineering teams to integrate AI models into production systems.
• Publish research findings in top-tier conferences and journals.
• Mentor junior researchers and contribute to a collaborative research environment.
• Work remotely, leveraging communication and collaboration tools to maintain high levels of productivity and team synergy. The opportunity to work from your preferred location within Bungoma, Bungoma, KE is provided with this role.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of hands-on experience in AI research and development, with a strong publication record in computer vision and deep learning.
• Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Keras).
• Solid understanding of linear algebra, calculus, probability, and statistics.
• Experience with cloud platforms (AWS, GCP, Azure) and distributed training is a plus.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences.
• Demonstrated ability to work independently and as part of a remote team.

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)

• Design, develop, and implement state-of-the-art AI and Machine Learning models.
• Perform data collection, preprocessing, and feature engineering for model training.
• Select, tune, and evaluate appropriate ML algorithms and deep learning architectures.
• Deploy ML models into production environments, ensuring scalability and performance.
• Collaborate with data scientists, engineers, and product managers to define project requirements.
• Stay abreast of the latest research and advancements in AI/ML.
• Develop and maintain robust documentation for models and systems.
• Mentor junior engineers and contribute to the team's technical growth.
• Troubleshoot and optimize AI/ML pipelines and infrastructure.
• Contribute to the company's intellectual property through innovative solutions.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of professional experience in AI/ML development.
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Strong understanding of statistical modeling, data mining, and data visualization.
• Excellent problem-solving, analytical, and critical thinking skills.
• Proven ability to work independently and manage multiple projects in a remote setting.
• Strong communication and collaboration skills, with the ability to explain complex technical concepts.

• Lead the design, development, and implementation of advanced computer vision algorithms and models for various applications.
• Conduct research into state-of-the-art computer vision techniques and propose novel solutions to complex problems.
• Develop and optimize deep learning models for tasks such as object detection, image segmentation, facial recognition, and image generation.
• Collaborate with cross-functional teams, including software engineers and product managers, to integrate AI/ML solutions into products and services.
• Manage and mentor a team of AI/ML engineers, providing technical guidance and fostering a collaborative environment.
• Oversee the data collection, annotation, and preparation process for training computer vision models.
• Implement robust testing and validation procedures to ensure the accuracy and reliability of AI models.
• Stay abreast of the latest advancements in AI, machine learning, and computer vision research, and actively contribute to the technical roadmap.
• Deploy and scale AI/ML models in production environments, ensuring performance and efficiency.
• Write high-quality, well-documented code in languages such as Python.
• Evaluate and select appropriate frameworks and tools for AI/ML development (e.g., TensorFlow, PyTorch).
• Contribute to intellectual property and publish research findings where appropriate.
• Troubleshoot and resolve complex technical issues related to AI/ML model performance and deployment.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 7 years of experience in AI/ML engineering, with a strong specialization in Computer Vision.
• Proven track record of developing and deploying complex computer vision models in production environments.
• Deep understanding of deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in Python and relevant libraries (e.g., OpenCV, NumPy, SciPy).
• Experience with cloud platforms (AWS, Azure, GCP) for AI/ML workloads.
• Strong knowledge of algorithms, data structures, and software engineering best practices.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong leadership and team management capabilities.
• Exceptional communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.
• Ability to work independently and collaboratively in a fully remote setting.
• Experience with model optimization and deployment strategies is highly desirable.