Build the future of African AI

Design, build, and deploy cutting-edge AI systems with deep expertise in LLM pipelines and video generation models. You will work at the intersection of research and production, optimizing inference, fine-tuning foundation models, and shipping AI-powered products at scale. Reports to the VP of Engineering / Head of AI.

Key Responsibilities

• Design, implement, and maintain end-to-end LLM inference and training pipelines using vLLM, TensorRT-LLM, and Triton Inference Server.
• Build and optimize video generation model pipelines (Stable Video Diffusion, Sora-class architectures, AnimateDiff, CogVideo) for real-time and batch inference.
• Implement model optimization: quantization (GPTQ, AWQ, GGUF), pruning, distillation, and speculative decoding.
• Deploy and manage GPU-accelerated inference on AWS, GCP, and Azure using Kubernetes, Docker, and NVIDIA NGC containers.
• Develop RAG systems integrating vector databases (Pinecone, Weaviate, Milvus, Qdrant) with LLM pipelines.
• Fine-tune foundation models (LLaMA, Mistral, Gemma, Qwen) using LoRA, QLoRA, DPO, RLHF, and SFT.
• Build evaluation frameworks and automated benchmarking for quality, latency, throughput, and cost.
• Implement multi-modal AI systems combining text, image, audio, and video generation.
• Design prompt engineering frameworks, guardrails, and safety layers for production.
• Collaborate with product, frontend, and backend teams to integrate AI into user-facing applications.

Required Qualifications

• Bachelor's or Master's in Computer Science, Machine Learning, Mathematics, or related field.
• 3+ years of production ML/AI experience.
• Deep expertise with LLM serving frameworks: vLLM, TensorRT-LLM, TGI, or llama.cpp.
• Strong experience with NVIDIA TensorRT, CUDA programming, and GPU optimization.
• Proficiency in Python and PyTorch, Hugging Face Transformers, DeepSpeed, Megatron-LM.
• Hands-on experience with diffusion/video generation models (Stable Diffusion, SDXL, SVD, ModelScope, AnimateDiff).
• Strong understanding of transformer architectures, attention mechanisms, MoE, SSM, Mamba.
• Experience with Docker, Kubernetes, CI/CD for ML, and MLOps tools (MLflow, W&B, DVC).

Nice to Have

• NVIDIA Triton Inference Server and custom backend development.
• Publications or open-source contributions.
• Distributed training (FSDP, DeepSpeed ZeRO), ONNX Runtime, edge deployment (Core ML, TensorRT).
• Experience with real-time AI streaming (WebSocket, gRPC, SSE) and AI safety / red-teaming.

Build beautiful, performant, and accessible user interfaces for our AI-powered products. Translate complex AI capabilities into intuitive experiences — from real-time chat to video generation dashboards and interactive model playgrounds. Reports to the Engineering Manager / CTO.

Key Responsibilities

• Architect scalable, responsive applications using React (Next.js) or Vue.js with TypeScript.
• Build real-time streaming UIs for LLM chat: token-by-token rendering, markdown, code highlighting.
• Design video generation preview interfaces with progress tracking, thumbnails, and playback.
• Develop reusable component libraries and design systems (Tailwind, Radix UI, shadcn/ui).
• Implement state management with Zustand, Jotai, Redux Toolkit, or TanStack Query.
• Optimize performance: code splitting, lazy loading, virtualized lists, Core Web Vitals.
• Consume REST and GraphQL APIs; implement WebSocket and SSE for real-time streaming.
• Write comprehensive tests (Vitest, Playwright, Testing Library); maintain 80%+ coverage.
• Implement OAuth 2.0, JWT, SSO flows and role-based access controls.
• Champion WCAG 2.1 AA accessibility, i18n, and progressive enhancement.

Required Qualifications

• Bachelor's in Computer Science, Software Engineering, or equivalent experience.
• 3+ years building production apps with React or Vue.js.
• Expert TypeScript and modern JavaScript (ES2022+).
• Next.js or Nuxt.js (SSR, SSG, API routes); Tailwind CSS.
• Vite, Webpack, or ESBuild; Git and CI/CD (GitHub Actions, GitLab CI).
• REST, GraphQL, WebSocket, and SSE familiarity.

Nice to Have

• AI/ML product UI experience (chat UIs, model dashboards).
• WebGL, Three.js, Canvas APIs; Framer Motion or GSAP.
• Monorepos (Turborepo, Nx), Storybook, or published npm packages.

Build the robust, scalable infrastructure powering our AI platform. Design high-throughput APIs, manage GPU-accelerated workloads, build async task systems, and ensure our services handle millions of requests. Reports to the Engineering Manager / CTO.

Key Responsibilities

• Design high-performance REST and GraphQL services with Python (FastAPI, Django) or Node.js (NestJS, Express).
• Build scalable microservices with service mesh, API gateway, and inter-service comms (gRPC, queues).
• Develop async task systems using Celery, Bull, or Temporal for long-running AI workloads.
• Design schemas across PostgreSQL, MongoDB, and Redis for high-throughput workloads.
• Implement real-time streaming APIs (WebSocket, SSE) for LLM token streaming.
• Build job queuing and GPU orchestration for batch and real-time inference.
• Design auth, multi-tenancy, RBAC, and API key management.
• CDN integration for large media (generated videos, images, artifacts).
• Monitoring with Prometheus, Grafana, ELK, or Datadog.
• CI/CD and IaC with Terraform, Pulumi, Docker, Kubernetes.

Required Qualifications

• Bachelor's or Master's in CS, Software Engineering, or equivalent.
• 4+ years of production backend experience.
• Strong Python (FastAPI, Django, Flask) and/or Node.js (TypeScript, NestJS).
• Deep expertise with PostgreSQL, MySQL, MongoDB, DynamoDB, Redis.
• Microservices at scale with Docker and Kubernetes.
• Distributed systems: CAP theorem, eventual consistency, Kafka, RabbitMQ, SQS.
• AWS, GCP, or Azure experience.

Nice to Have

• Backend for AI/ML (model serving, inference APIs, training pipelines).
• GPU resource management and NVIDIA infrastructure.
• Event-driven / CQRS; GraphQL federation; serverless (Lambda, Cloud Functions).

Build and maintain the data infrastructure that fuels our AI models and products. Design robust pipelines, manage large-scale datasets for training and evaluation, and build the data platform that enables the whole organization. Reports to the Head of Data / VP of Engineering.

Key Responsibilities

• Design scalable ETL/ELT pipelines with Airflow, Dagster, Prefect, or dbt.
• Build data lakes and warehouses on Snowflake, BigQuery, Redshift, or Databricks.
• Develop ingestion pipelines from APIs, web scraping, Kafka/Kinesis, databases, and files.
• Curate training datasets for LLM fine-tuning and video generation with quality controls and versioning.
• Implement data quality frameworks: validation, anomaly detection, lineage, profiling.
• Real-time streaming with Kafka, Flink, or Spark Structured Streaming.
• Optimize storage: partitioning, compression, Parquet, Delta Lake, Iceberg.
• Build feature stores and serving layers for training and inference.
• Data governance, cataloging, and access control.
• Pipeline health dashboards and SLA monitoring.

Required Qualifications

• Bachelor's or Master's in CS, Data Engineering, or related technical field.
• 3+ years of production data engineering experience.
• Strong Python and SQL; Spark (PySpark), Pandas.
• Airflow, Dagster, Prefect, or dbt.
• Snowflake, BigQuery, Databricks, or Redshift.
• Kafka, Flink, Kinesis, or Pub/Sub.
• AWS, GCP, or Azure; Terraform or CloudFormation.

Nice to Have

• Pipelines for AI/ML training (dataset curation, labeling, versioning).
• Vector databases (Pinecone, Weaviate, Qdrant); lakehouse (Delta, Iceberg, Hudi).
• Neo4j and knowledge graphs; large-scale scraping (Scrapy, Playwright).
• GDPR / CCPA and PII handling best practices.

For ambitious recent graduates who want to launch their careers at the forefront of artificial intelligence. Over 12–18 months, rotate through multiple departments — engineering, product, data, marketing, and operations — with a senior mentor, structured training, and real projects with measurable impact. Reports to the Program Coordinator / Department Heads.

Key Responsibilities

• Complete structured rotations across 3–4 departments over the program duration.
• Contribute to live projects under senior guidance, delivering tangible outputs each rotation.
• Participate in weekly learning sessions covering AI fundamentals, business strategy, and professional skills.
• Present rotation learnings and project outcomes to leadership at the end of each cycle.
• Collaborate cross-functionally on hackathons and innovation sprints.
• Maintain a learning journal and personal development plan with your mentor.
• On completion, transition into a permanent role aligned with your demonstrated strengths.

Required Qualifications

• Bachelor's degree (completed within the last 2 years) in CS, Engineering, Business, Data Science, Marketing, or related.
• Strong academic record and demonstrated passion for technology and innovation.
• Excellent written and verbal communication.
• Analytical mindset, problem-solving skills, attention to detail.
• Self-motivated, curious, eager to learn across domains.
• Basic proficiency in Python, JavaScript, or SQL is a plus.

Nice to Have

• Prior internship at a technology or AI company.
• Hackathons, coding competitions, or open-source participation.
• Leadership in student organizations; blog posts or personal projects.

Note: This is a re-advertisement. Previous applicants need not re-apply.

Gain hands-on experience at a leading AI company. Interns are embedded in working teams, contributing to real projects across engineering, data, product, marketing, or business operations. Paid internship with possible conversion to a full-time role or the Graduate Trainee Program based on performance. Reports to your assigned Supervisor / Team Lead.

Key Responsibilities

• Support your team with day-to-day tasks, project deliverables, and research.
• Assist engineers with coding, testing, documentation, data labeling, or model evaluation (technical tracks).
• Help create marketing content, social campaigns, market research, and competitive analysis (business tracks).
• Participate in sprint planning, retrospectives, and company-wide knowledge sharing.
• Collaborate on a capstone group project presented to leadership at the end of the internship.
• Attend structured workshops on AI fundamentals and professional development.

Required Qualifications

• Currently enrolled in or recently completed a Bachelor's or Master's degree in a relevant field.
• Strong academic performance and genuine interest in AI and technology.
• Good communication and teamwork skills.
• Proactive attitude, willingness to learn, ability to take initiative.
• Technical tracks: basic knowledge of Python, JavaScript, or SQL.
• Business tracks: strong writing, analytical thinking, social media familiarity.
• Able to commit to the full 3–6 month duration.

Nice to Have

• Previous internship or volunteer experience.
• Portfolios, GitHub profiles, or personal projects.
• Familiarity with AI tools (ChatGPT, Midjourney) and data tools (Excel, Tableau, Power BI).

Manage and strengthen our financial operations as we scale. Maintain accurate records, prepare reports, manage payroll and tax compliance, and support budgeting and forecasting. Critical to financial transparency, regulatory compliance, and sound fiscal management. Reports to the Head of Finance / CFO.

Key Responsibilities

• Prepare financial statements, general ledger entries, and monthly/quarterly/annual closing reports.
• Manage accounts payable and receivable; timely invoicing, payments, and collections.
• Process payroll with statutory deductions, benefits, and labor law compliance.
• Prepare and file tax returns (corporate, VAT/GST, withholding) and ensure compliance.
• Bank reconciliations, petty cash, and inter-company account reconciliations.
• Support budgeting and forecasting with accurate data and variance analysis.
• Assist with internal and external audits.
• Maintain fixed asset registers, depreciation, and disposal records.
• Implement internal financial controls; monitor cash flow and projections.
• Stay current with IFRS, tax legislation, and regulatory requirements.

Required Qualifications

• Bachelor's in Accounting, Finance, or related.
• CPA, ACCA, CMA, or equivalent (fully or partially qualified).
• 3+ years of accounting experience, preferably in tech or a fast-growing company.
• Proficiency in QuickBooks, Xero, Sage, or SAP; advanced Excel.
• Thorough knowledge of IFRS, local tax laws, and reporting standards.
• Excellent attention to detail, accuracy, and organizational skills.

Nice to Have

• Cloud accounting platforms and financial automation tools.
• Multi-currency and international operations.
• Fundraising, investor reporting, and due diligence exposure.
• ERP systems and Power BI / Tableau.

Provide comprehensive legal counsel and ensure regulatory compliance across all aspects of our operations. Advise on contracts, IP, data privacy, employment law, corporate governance, and AI-specific regulatory matters. As our sole legal hire, play a foundational role in building the legal framework. Reports to the Head of Legal / CEO.

Key Responsibilities

• Draft, review, and negotiate SaaS agreements, NDAs, vendor, partnership, and licensing contracts.
• Advise on IP strategy: patents, trademarks, copyrights, and trade secrets related to AI models.
• Ensure compliance with GDPR, CCPA, and local data protection laws.
• Monitor and advise on emerging AI regulations and responsible AI frameworks.
• Support corporate governance: board resolutions, shareholder agreements, company secretarial, regulatory filings.
• Advise on employment law: contracts, policies, disciplinary and termination procedures.
• Manage external law firms on litigation, IP filings, and regulatory submissions.
• Develop internal legal templates, policies, and compliance checklists.
• Conduct legal risk assessments for new products, features, markets, and partnerships.
• Support fundraising: term sheets, investment agreements, due diligence.
• Handle dispute resolution, mediation, and litigation.

Required Qualifications

• LLB from a recognized university; admission to the relevant Bar / Law Society.
• 4+ years post-qualification experience, preferably in tech or startups.
• Strong commercial contract drafting, review, and negotiation.
• Solid IP law knowledge relating to software, AI models, and digital assets.
• Working knowledge of GDPR, CCPA, or equivalent frameworks.
• Corporate and commercial law, company secretarial, regulatory compliance.
• Excellent research, analytical reasoning, and written communication.

Nice to Have

• LLM with specialization in Technology Law, IP, or Data Privacy.
• Experience advising AI or tech companies on regulatory matters.
• Cross-border transactions; VC fundraising support.
• Open-source licensing (MIT, Apache, GPL) and its implications for AI distribution.

Drive brand awareness, user acquisition, and revenue growth for our AI products. Develop and execute multi-channel strategies across content, SEO/SEM, social, email, launches, and community. A blend of creative storytelling and data-driven decision-making. Reports to the Head of Marketing / CMO.

Key Responsibilities

• Develop comprehensive marketing strategies aligned with company goals and launches.
• Plan, create, and manage content across blogs, whitepapers, case studies, newsletters, social, and video.
• Manage paid ads (Google, LinkedIn, Meta, X) with a focus on ROI and conversion.
• Drive SEO: keyword research, on-page, link building, and technical SEO.
• Build email campaigns and automated nurture sequences (HubSpot, Mailchimp, SendGrid).
• Grow social presence across LinkedIn, X, YouTube, Reddit, Hacker News, and Discord.
• Plan product launches, webinars, conferences, and community events.
• Maintain brand guidelines, messaging frameworks, and positioning.
• Analyze CAC, LTV, conversion, engagement; produce actionable reports.
• Collaborate with product, sales, and engineering on go-to-market strategies.
• Manage PR agencies, influencers, media, and analysts.

Required Qualifications

• Bachelor's in Marketing, Communications, Business, or related.
• 3+ years in digital marketing, preferably B2B SaaS, tech, or AI.
• Proven multi-channel campaign track record.
• Strong SEO/SEM, Google Analytics, Google Search Console, and paid ads expertise.
• HubSpot, Salesforce, or Mailchimp proficiency.
• Excellent copywriting; ability to simplify technical topics.
• Data-driven mindset with A/B testing and optimization experience.

Nice to Have

• Marketing AI, ML, or developer-focused products.
• Developer relations (DevRel) and technical community building.
• Video production and YouTube for tech content.
• Product-led growth (PLG) and freemium conversion.
• Affiliate, partner, or influencer programs in tech.