1,836 Machine Learning Consultant jobs in Kenya

• Assist in collecting, cleaning, and organizing large datasets from various sources.
• Perform basic data analysis and generate reports under the guidance of senior analysts.
• Develop and maintain data visualizations to help communicate insights effectively.
• Support the development of dashboards and reports using business intelligence tools.
• Conduct research on industry trends and competitive landscape to inform analytical projects.
• Collaborate with team members on ad-hoc data analysis requests.
• Learn and apply statistical methods and data modeling techniques.
• Participate in team meetings and contribute ideas for data-driven solutions.
• Assist in documenting data sources, methodologies, and findings.
• Gain exposure to programming languages commonly used in data analysis, such as Python or R.

• Recent graduate with a Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Data Science, or a related discipline.
• Strong analytical and problem-solving skills.
• Proficiency in Microsoft Excel for data manipulation and analysis.
• Basic understanding of statistical concepts and data analysis principles.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Exposure to programming languages like Python or R is highly desirable.
• Excellent written and verbal communication skills.
• Ability to work independently and manage tasks effectively in a remote setting.
• Eagerness to learn and a strong work ethic.
• Enthusiasm for data and analytics.

• Define and drive the product vision, strategy, and roadmap for AI/ML products.
• Conduct market research, competitive analysis, and customer interviews to identify user needs and opportunities.
• Translate product strategy into detailed product requirements, user stories, and specifications.
• Prioritize product backlog and manage development sprints in collaboration with engineering teams.
• Work closely with data scientists and machine learning engineers to guide the development of AI models and features.
• Define key product metrics, monitor performance, and iterate on products based on data and user feedback.
• Collaborate with marketing and sales teams to develop go-to-market strategies and product launch plans.
• Engage with customers and internal stakeholders to gather feedback and ensure product-market fit.
• Stay abreast of the latest advancements in AI, machine learning, and relevant technologies.
• Mentor junior product managers and contribute to the product management best practices within the organization.
• Develop and maintain strong relationships with engineering, design, research, and business teams.
• Manage product lifecycle from ideation to launch and ongoing iteration.

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field; Master's degree or MBA preferred.
• Minimum of 7 years of experience in product management, with a significant focus on AI/ML products or related technologies.
• Proven experience in defining product strategy, roadmaps, and successfully launching complex software products.
• Strong technical understanding of machine learning concepts, algorithms, and frameworks.
• Experience working in agile development environments.
• Excellent analytical, problem-solving, and strategic thinking skills.
• Superb communication, presentation, and interpersonal skills.
• Ability to lead cross-functional teams and influence without direct authority.
• Experience with user research, usability testing, and data analysis.
• Passion for AI and a deep understanding of its potential applications.
• Demonstrated ability to work effectively in a fully remote setting.

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.

About Tally

Tally is an AI-powered recruiting copilot developed by Nexa Consulting. Launching in January 2026, Tally

helps recruiters and startup founders save time by parsing CVs, matching candidates, and generating

interview insights. Our mission is to redefine recruiting efficiency and empower users worldwide.

Role

We are looking for a Community & Content Manager to shape and scale Tally's voice across digital

channels, engage with our growing community of recruiters and startup founders, and create content

that educates, inspires, and converts. You will work closely with our Growth Marketer to ensure content

and campaigns are fully aligned for maximum impact.

Responsibilities

• Plan, write, and publish high-quality content (LinkedIn posts, blog articles, newsletters, case studies).

• Create copy and visuals that make AI recruiting features simple and relatable.

• Support growth campaigns with landing page copy, ad creatives, and nurturing emails.

• Build and manage Tally's presence on LinkedIn and other relevant platforms.

• Respond to comments, DMs, and questions, fostering trust with early adopters.

• Organize webinars, demos, and community events to showcase product value.

• Collaborate with the Growth Marketer to align content with acquisition strategies.

• Track engagement metrics and optimize based on results.

Requirements (Must-Haves)

• 3+ years in content marketing, community management, or communications.

• Excellent copywriting skills in English (short and long form).

• Strong understanding of LinkedIn as a growth channel.

• Experience in building and engaging online communities.

• Startup mentality: proactive, creative, comfortable with fast iteration.

Nice-to-Haves

• Experience in HR Tech or SaaS.

• SEO/content optimization skills.

• Familiarity with tools like HubSpot, Hootsuite, Buffer.

• Basic design or video editing skills.

KPIs

• Growth in LinkedIn audience & engagement rate.

• Number of inbound leads generated via content.

• Community activity (webinar attendance, testimonials).

• Contribution to growth campaigns (content delivery & performance).

• Define and manage the roadmap for AI platform development, including ML infrastructure, data pipelines, and MLOps tools.
• Lead cross-functional teams comprising data scientists, ML engineers, software developers, and researchers to deliver AI solutions.
• Develop detailed project plans, including scope, timelines, resource allocation, and risk assessment.
• Drive execution excellence by effectively managing dependencies, mitigating risks, and ensuring timely delivery of project milestones.
• Facilitate clear and concise communication across all levels of the organization, including executive leadership, technical teams, and external stakeholders.
• Champion best practices in Agile methodologies, AI/ML development, and MLOps.
• Identify and address technical challenges and roadblocks, working collaboratively with engineering teams to find innovative solutions.
• Manage vendor relationships and evaluate third-party tools and technologies relevant to AI platforms.
• Define and track key performance indicators (KPIs) to measure the success and impact of AI initiatives.
• Mentor junior program managers and contribute to the growth of the program management function within the organization.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
• 7+ years of experience in program management, with a significant focus on AI/ML projects and platforms.
• Deep understanding of machine learning concepts, algorithms, and the end-to-end ML lifecycle.
• Proven experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Strong knowledge of software development lifecycles, Agile/Scrum methodologies, and MLOps principles.
• Demonstrated success in managing complex, cross-functional technical projects with ambiguity.
• Excellent analytical, strategic thinking, and problem-solving skills.
• Exceptional leadership, communication, and stakeholder management abilities.
• Experience working in a remote or distributed team environment is highly desirable.

• Lead the planning, execution, and delivery of AI and emerging technology projects.
• Define project scope, goals, and deliverables in collaboration with senior management and stakeholders.
• Develop and manage detailed project plans, timelines, and budgets.
• Assemble and lead high-performing, remote project teams.
• Facilitate effective communication and collaboration among team members and stakeholders.
• Identify, assess, and manage project risks and issues.
• Monitor project progress and performance, implementing corrective actions as needed.
• Ensure projects are completed on time, within scope, and to the highest quality standards.
• Manage stakeholder expectations and provide regular project status updates.
• Drive adoption of new technologies and methodologies.

• Bachelor's degree in Computer Science, Engineering, Project Management, or a related field. Master's degree or PMP/Agile certification preferred.
• Minimum of 7 years of experience in project management, with a significant focus on technology and AI projects.
• Proven experience managing complex, multi-disciplinary projects in a remote setting.
• In-depth knowledge of AI, machine learning, and other emerging technologies.
• Strong understanding of project management methodologies (Agile, Scrum, Waterfall).
• Excellent leadership, communication, and negotiation skills.
• Proficiency with project management software (e.g., Jira, Asana, MS Project).
• Demonstrated ability to manage budgets and resources effectively.
• Strong analytical and problem-solving skills.
• Ability to work independently and as part of a distributed team.

• Assist in collecting, cleaning, and transforming large datasets from various sources.
• Perform exploratory data analysis (EDA) to identify patterns, trends, and anomalies.
• Support the development and testing of machine learning models and algorithms under supervision.
• Create compelling data visualizations and dashboards to communicate findings to stakeholders.
• Contribute to the documentation of data processes, methodologies, and code.
• Collaborate with senior data scientists and analysts on ongoing projects.
• Learn and apply statistical concepts and data mining techniques.
• Participate in team meetings and contribute ideas for data-driven solutions.
• Assist in preparing reports and presentations summarizing analytical results.
• Develop proficiency in data analysis tools and programming languages relevant to data science.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Strong understanding of statistical concepts and analytical techniques.
• Basic knowledge of programming languages commonly used in data science (e.g., Python, R).
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Excellent analytical and problem-solving skills.
• Strong attention to detail and ability to work with large datasets.
• Good communication and interpersonal skills, with the ability to work effectively in a remote team.
• Eagerness to learn and a proactive attitude.
• Ability to manage tasks and time effectively.
• Passion for data and uncovering insights.

• Lead the planning, execution, and delivery of AI integration projects.
• Define project scope, objectives, deliverables, and success criteria in collaboration with stakeholders.
• Develop comprehensive project plans, including schedules, resource allocation, and budget management.
• Manage project risks and issues, implementing mitigation strategies and contingency plans.
• Facilitate effective communication and collaboration among cross-functional teams (engineering, data science, product, QA).
• Ensure adherence to agile development methodologies and best practices.
• Monitor project progress, track key performance indicators (KPIs), and provide regular status reports to senior leadership.
• Manage vendor relationships and third-party integrations as needed.
• Ensure that AI solutions meet technical requirements, quality standards, and business objectives.
• Drive continuous improvement in project management processes and team performance.

• Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's degree preferred.
• Minimum of 7 years of experience in technical project management, with a proven track record of delivering complex software projects.
• Demonstrated experience managing projects involving Artificial Intelligence, Machine Learning, or Data Science.
• Strong understanding of AI/ML concepts, algorithms, and deployment strategies.
• Expertise in agile project management methodologies (Scrum, Kanban).
• Excellent leadership, communication, negotiation, and interpersonal skills.
• Proficiency in project management tools such as Jira, Asana, or Microsoft Project.
• Ability to translate technical concepts into business terms and vice versa.
• Experience working in a hybrid work environment.
• PMP or equivalent project management certification is a plus.