Jobs in Mauritius
Computational Linguist Annotator (Maurice)
JOB TITTLE : Computational linguist Annotator LOCATION: Remote (Worldwide) EMPLOYMENT TYPE: Full Time JOB SUMMARY We are seeking a highly motivated Computational Linguist with strong expertise in linguistic annotation and natural language processing (NLP). In this role, you will design, implement, and evaluate annotation frameworks that support the development of advanced AI language systems. You will work closely with machine learning engineers, data scientists, and annotation teams to ensure high-quality linguistic datasets. Key Responsibilities • Design linguistic annotation schemas for complex NLP tasks including semantic role labeling, discourse parsing, coreference resolution and multimodal language. • Develop comprehensive annotation guidelines that balance linguistic precision with annotator usability and scalability. • Collaborate with new product teams to translate business requirements into linguistic annotation frameworks. • Ensure schemas capture relevant linguistic phenomena while remaining computationally tractable. • Build and maintain annotation interfaces, quality assurance dashboards and data management tools. • Develop scripts and utilities for data preprocessing, validation and analysis. Requirements • Bachelor's degree in Linguistics, English or a relating field. • Minimum 5 years’ experience in computational linguistics, language annotation, or NLP data operations. • Strong academic foundation in syntax, semantics, pragmatics and discourse analysis. • Experience in building and customizing annotation tools and work flows. • Track record in managing annotation projects from pilot to production scale. • Excellent written and verbal communication skills.
Machine Learning Engineer
Key Responsibilities: • Adapt and deploy existing machine learning (ML) models. • Integrate processing pipelines into Airflow and through APIs (Investigation Center interface). • Prepare and transform data stored in MinIO and PostgreSQL. • Optimize PySpark code for generating monthly alerts. • Manage dependencies, sequences, and stages within ML workflows. Technical Environment: • Technologies: Airflow, GitLab, PySpark • Nice-to-have Technologies: MinIO, PostgreSQL, Jupyter, MLFlow Benefits: • Competitive salary and benefits package. • Opportunities for continuous learning and professional growth. • A collaborative and inclusive work environment. • Exposure to cutting-edge technologies and innovative projects. • Supportive leadership and career development programs. Required Skills and Qualifications: • 5+ years of experience in data engineering, ML Engineer or related roles. • Degree holder – Information Technology, Software Engineering, Data Science or any other related courses • Strong proficiency in PySpark and code optimization. • Knowledge of ML workflows, including the ability to manage dependencies and sequencing, as well as Airflow pipelines. • Good understanding of PostgreSQL databases and MinIO object storage. • Familiarity with GitLab and Jupyter. • Fluent in French and English (for international collaboration and communication).
Machine Learning Engineer (Maurice)
About The Team As a Machine Learning Engineer within Zillow’s Rich Media Virtual Staging AI team, you’ll join a group focused on helping people better understand homes through immersive, AI-powered experiences. The team works on turning photos, video, and spatial signals into structured representations that power customer-facing products used by millions of shoppers. Within Rich Media, the VSAI team is building systems that transform home media into products that enrich the understanding of a home. About The Role This is a high-impact individual contributor role for someone who loves operating at the intersection of modeling and systems. As a Machine Learning Engineer, you’ll help shape how Zillow builds production-grade machine learning systems for rich media experiences, partnering across applied science and engineering to turn promising ideas into reliable, scalable product capabilities. You Will Get To: • Productionalization: Owning the transition from research code to production-ready and optimized models. Establishing CI/CD pipelines that allow scientists to deploy models in short iteration cycles. Innovating upon our existing monitoring systems that make our services reliable and give scientists insight into the performance of their models in production. Designing services to expose ML models to Zillow’s end customers • Data: Good data is key to many SOTA ML methods. You will own our team’s datasets, lead and support data engineering projects, understand datasets from other teams, and collaborate with scientists and other teams to prepare them for model training. • Training & Experimentation: Owning projects and supporting scientists in running large-scale training and data processing by collaborating with them on specific projects, establishing generalized best practices, and sharing expertise around performance and software engineering principles, while leveraging AI coding and productivity tools. • Modeling: Staying on top of cutting-edge research (for example, on platforms like Arxiv, X, and Papers With Code) and modifying its methods for our use cases in innovative ways to enable new product experiences or improve existing ones. • Dev & MLOps: Establishing best practices around code quality, testing, and ownership that allow us to move fast without compromising reliability (and sleep). Participating in our existing on-call rotation This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions. In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside. Who you are • You have 1-3 years professional experience building and shipping machine learning models or ML-powered systems in production. • You have strong hands-on proficiency in Python and at least one modern machine learning framework, such as PyTorch, JAX or TensorFlow. • You have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes) • You have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems) • You have experience using backend code languages such as TypeScript or Go to fully implement ML-powered systems end-to-end • You have experience building and operating end-to-end machine learning workflows, including data pipelines, model training, evaluation, deployment, and monitoring. • You have a strong foundation in machine learning fundamentals such as representation learning, structured prediction, computer vision, optimization, and failure analysis. • You are comfortable debugging model and system behavior in real-world environments and using metrics, logs, and experiments to improve outcomes. • You collaborate effectively with applied scientists, software engineers, and product partners in ambiguous, cross-functional settings. • You have strong engineering judgment and know how to balance experimentation with reliability, speed, and long-term maintainability. • You communicate technical ideas clearly and can influence decisions across disciplines. Nice to have • Experience in computer vision, spatial data, 3D, AR/VR, or related domains is a plus. Get to know us At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality. Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow. No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together. Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Data Scientist
About The Role Own the creation of decision‑grade intelligence products by applying advanced analytics and statistics to transform complex multi‑source data into trusted, monetizable customer offerings Key Responsibilities Analytics & Modelling • Design, build, validate, and maintain predictive and prescriptive models across travel, risk, and location domains • Apply statistical methods, machine learning, and experimentation to improve data accuracy, completeness, and trust • Develop domain‑specific metrics, benchmarks, and risk scoring frameworks Product & Commercial Responsibilities • Translate customer problems and market needs into analytical solutions and data products • Partner with Product Managers to define value propositions, pricing inputs, and success metrics • Contribute to roadmap prioritisation based on impact, feasibility, and monetisation potential Data Quality, Governance & Ethics • Define data quality rules, validation logic, and anomaly detection mechanisms • Ensure alignment with privacy, consent, and ethical AI standards in regulated environments • Support lineage, explainability, and auditability of analytical outputs Collaboration & Delivery • Work closely with Data Engineers to ensure model‑ready, reliable data pipelines • Collaborate with Machine Learning Engineers to operationalise models at scale • Communicate insights and recommendations clearly to technical and non‑technical stakeholders Job Profile – Required Skills And Knowledge • 7-8+ years' experience in applied data science roles • Strong proficiency in Python, SQL, and ML libraries • Ability to translate data into presentable stories. • Experience delivering customer‑facing, revenue‑generating data products Required Qualifications • Bachelor’s degree in computer science, Engineering, Information Systems, or related field • MS in AI, Big Data or relevant fields.
A.I Policy Reviewer (Maurice)
Job Title: AI Policy Reviewer Location: Remote (Worldwide) Job Summary: The AI Policy Reviewer is responsible for evaluating AI-generated and user-generated content to ensure compliance with internal governance standards, regulatory requirements, and responsible AI principles. This role plays a key part in safeguarding model integrity by reviewing outputs for safety risks, bias, misinformation, harmful content, and policy violations, while ensuring consistent enforcement of AI usage guidelines. Responsibilities • Review and score AI-generated responses against detailed policy rubrics. Assess outputs for safety, truthfulness, fairness, and alignment with community guidelines. • Act as a quality assurance checkpoint for automated systems. Identify instances where the AI misinterprets policy (e.g., being over-sensitive and censoring benign content, or under-sensitive and allowing harmful content). • Handle complex “edge cases” where policy application is ambiguous. Make nuanced judgement calls regarding context, satire, or emerging risks that the AI model struggles to process. • Analyze and review data to identify systematic flaws in the AI’s reasoning. Report patterns of bias, hallucination, or policy gaps to the Product and Engineering teams. • Collaborate with Policy teams to test and refine evaluation rubrics. Provide feedback on whether current policies are “teachable” to AI models or if they require human-only judgement. • Participate in adversarial testing (red teaming) by attempting to “jailbreak” the model or provoke unsafe responses to identify vulnerabilities before launch. • Work closely with Machine Learning Engineers to explain the “why” behind your ratings, helping them adjust model behavior. • Write high-quality examples (prompts and ideal responses) that’s serve as “golden sets” for training the AI on how to handle difficult policy scenarios. Requirements • Minimum of 3 years of professional experience in Trust & Safety Operations, Content Policy, Risk Analysis, or Legal/Compliance review. • Deep understanding of content moderation principles, including hate speech, harassment, misinformation, and graphic violence policies. • Strong ability to deconstruct complex AI responses and identify logical flaws, hallucinations, or subtle biases. • Clear and concise written communication skills. You must be able to explain why an AI response was wrong in a way that engineers and policy experts can understand. • This role involves exposure to disturbing AI-generated text and images designed to test safely limits. Proven emotional resilience and self-care strategies are required. • Comfortable working with dashboards, spreadsheets, and specialized review tools. Familiarity with LLMs (ChatGPT, Gemini, etc.). • Proven ability to follow complex, detailed instructions and scoring rubrics with high consistency and accuracy. • Understanding of global cultural and political nuances to assess whether AI responses are appropriate for diverse international audiences.
RLHF Specialist (Maurice)
Job Title: RLHF Specialist Location: Remote (Worldwide) Job Summary: An RLHF Specialist is responsible for improving and aligning AI models using Reinforcement Learning from Human Feedback (RLHF) methodologies. This role focuses on designing, implementing, and optimizing feedback pipelines that enhance model performance, safety, factual accuracy, and alignment with human values. Responsibilities • Generate high-quality preference data by comparing multiple model responses and ranking them based on criteria such as helpfulness, honesty, and harmlessness (HHH). • Design complex, multi-turn prompts to stress-test model behavior and expose weaknesses in reasoning or safety. • Write detailed “chain-of-thought” explanations and rationales to train reward models on why specific responses are superior. • Collaborate with Machine Learning Engineers to analyze model failure modes and identify data gaps that, when filled, will improve reinforcement learning outcomes. • Develop and iterate on annotation strategies for preference scoring and reinforcement signals, ensuring consistency across a global team. • Proactively probe models to identify vulnerabilities, biases, or hallucination patterns, documenting findings for model optimization. • Analyze edge cases where the reward model behaves unexpectedly (e.g., over-indexing on verbosity or style over substance). Provide detailed feedback to ML engineers on reward model failure modes and suggest specific data interventions to correct model behavior. • Develop and document templated instruction sets for larger annotation teams. Translate complex reinforcement learning concepts into simple, repeatable tasks for junior reviewers, ensuring high-quality data collection at scale. • Monitor model performance over time by maintaining a personal test set of prompts. Regularly re-evaluate new model versions against historical benchmarks to track improvements or regressions in reasoning and alignment. Requirements • Minimum of 2 years of experience in Data Annotation, Model Evaluation, Computational Linguistics, or Trust and Safety, specifically working with AI/ML training data. • Strong proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow). • Deep understanding of Reinforcement Learning concepts (PPO, Trust Regions, Reward Hacking) and how they apply to language generation. • Hands-on experience fine-tuning open-source models (e.g., Llama 2/3, Mistral, gemma) using techniques like LoRA/QLoRA. • Experience working with annotation tools (LabelBox, Scale AI, Snorkel) and managing human-in-the-loop workflows. • Ability to diagnose why an RL policy collapsed and adjust hyperparameters or reward structure accordingly. • Experience with Constitutional AI or Self-Alignment techniques. • Contributions to open-source alignment libraries (TRL, Transformer Reinforcement Learning, Axolotl). • Experience with cloud Platforms (AWS SageMaker, GCP Vertex AI).
A place to build useful ways of working with artificial intelligence.
A teaching approach aimed at usage, not knowledge.
Document Analyst (Maurice)
Job Title: Document Analyst Location: Remote (Worldwide) Job Summary: The Document Analyst is responsible for reviewing, verifying, and analyzing documents to ensure accuracy, authenticity, completeness, and compliance with organizational policies and regulatory standards. This role supports operational integrity by identifying discrepancies, validating information, and assessing documentation for potential risk, fraud, or procedural gaps. Responsibilities • Analyze and validate data extracted from a wide variety of documents, including government-issued IDs, proof of address, financial statements, legal contracts, and medical forms. Ensure extracted fields (name, date, document number, etc.) are accurate and complete. • Identify sophisticated document fraud, including photoshopped IDs, counterfeit documents, and deepfake verification attempts. Use forensic analysis techniques to spot anomalies in security features (holograms, watermarks, microprint). • Handle complex edge cases where documents are damaged, non-standard, or from unfamiliar jurisdictions. Use research skills and domain knowledge to make accurate determinations on document validity and data interpretation. • Collaborate with Policy and Product teams to create, test, and refine annotation guidelines account for global document diversity and emerging fraud vectors. • Provide structured feedback to machine learning engineers and data scientists on model performance. Identify systematic errors in OCR or data extraction and contribute to “golden datasets” used for model training and evaluation. • Perform quality checks on document annotations and verifications completed by junior analysts or automated systems. Maintain high inter-annotator agreement (IAA) and ensure compliance with regulatory requirements. • Ensure document processing workflows comply with global regulations, including KYC (Know Your Customer), AML (Anti-Money Laundering), GDPR, and eIDAS (Electronic Identification and Trust Services). • Identify opportunities to streamline document review workflows, improve tooling, and reduce manual touchpoints without compromising accuracy or security. Requirements • Minimum of 3 years of experience in Document Analysis, Identity verification, KYC/AML Operations, or Data Extraction within fintech, legal tech, trust & safety, or AI training sectors. • Deep knowledge of global identity documents (passports, driver’s licenses, national IDs), financial documents (bank statements, pay stubs), and/or legal documents (contracts, incorporation papers). • Proven ability to identify sophisticated document fraud, including manipulation techniques, forgery indicators, and biometric discrepancies. • Experience with document verification tools, OCR software, or annotation platforms. Familiarity with data formats such as JSON, XML, or CSV for structured data output. • Strong understanding of KYC/AML frameworks, data privacy regulations (GDPR, CCPA) and industry standards for identity verification.