ai engineer

ai/ml specialists (data scientists/ ml engineer) Jobs in Bahrain

ai/ml specialists (data scientists/ ml engineer)

data scientist (core ai / nlp engineering) Jobs in Bahrain

data scientist (core ai / nlp engineering)

data scientists - banking Jobs in Bahrain

data scientists - banking

internship - (software engineer & ai engineer) Jobs in Bahrain

internship - (software engineer & ai engineer)

data scientist core ai nlp engineering

TAT IT Technolgies

<div>
 
 Urgent requirement for Data Scientist (
 
 
 Core AI / NLP Engineering) is required for our client in Bahrain
 
 
 
 
 Design and develop machine learning models to support AI-driven banking solutions is MUST
 
 
 
 
 Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.) is MUST
 
 
 
 
 LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks is MUST
 
 
 
 
 Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy) is MUST
 
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and develop machine learning models to support AI-driven banking solutions
 </li>
 <li>
 Collaborate with data engineers to access and prepare data for modeling
 </li>
 <li>
 Apply statistical and ML techniques to solve business problems (e.g., churn prediction, credit
 </li>
 <li>
 scoring)
 </li>
 <li>
 Evaluate model performance and optimize for accuracy, precision, and recall
 </li>
 <li>
 Deploy models into production using MLOps frameworks and CI/CD pipelines
 </li>
 <li>
 Ensure models are explainable, auditable, and compliant with regulatory standards
 </li>
 <li>
 Work with business stakeholders to identify AI opportunities and define success metrics
 </li>
 <li>
 Document model assumptions, data sources, and performance benchmarks
 
 
 </li>
 </ul>
 Core AI / NLP Engineering
 
 
 <ul>
 <li>
 Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)
 </li>
 <li>
 LLM fine-tuning (LoRA, PEFT, prompt tuning)
 </li>
 <li>
 Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)
 </li>
 <li>
 Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)
 </li>
 <li>
 Knowledge of embeddings, tokenization, and transformer architecture
 </li>
 <li>
 Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch
 </li>
 <li>
 Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)
 
 
 </li>
 </ul>
 Software Engineering &amp; Backend Integration
 
 
 <ul>
 <li>
 RESTful and GraphQL APIs, webhooks
 </li>
 <li>
 Containerization and deployment (Docker, Kubernetes, CI/CD)
 </li>
 <li>
 Authentication and user/session management
 </li>
 <li>
 Data pipelines and microservices
 </li>
 <li>
 Knowledge of frameworks like FastAPI, Flask, NestJS, or Express
 </li>
 <li>
 Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)
 
 
 </li>
 </ul>
 Agent Orchestration &amp; Tooling
 
 
 <ul>
 <li>
 LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks
 </li>
 <li>
 Task-decomposition and reasoning chains
 </li>
 <li>
 Function calling, tool use, and API chaining
 </li>
 <li>
 Memory design (short-term vs long-term)
 </li>
 <li>
 Context management and grounding strategies
 
 
 </li>
 </ul>
 Conversational UX / Design
 
 
 <ul>
 <li>
 Conversation design frameworks (Google CCAI, Microsoft Bot Framework, Voiceflow, Botpress)
 </li>
 <li>
 Flow design and intent management (Dialogflow, Rasa, Cognigy)
 </li>
 <li>
 Tone, empathy, and personality design for AI personas
 </li>
 <li>
 A/B testing dialogue variants and measuring user satisfaction
 
 
 </li>
 </ul>
 Data &amp; Infrastructure
 
 
 <ul>
 <li>
 Data pipelines (Airflow, dbt, Kafka)
 </li>
 <li>
 Structured/unstructured data ingestion (PDFs, databases, APIs)
 </li>
 <li>
 Feature store and model registry management (MLflow, Kubeflow)
 </li>
 <li>
 Vector database deployment and optimization
 </li>
 <li>
 Monitoring, logging, and drift detection
 
 
 </li>
 </ul>
 Governance, Security &amp; Compliance
 
 
 <ul>
 <li>
 Model explainability (SHAP, LIME)
 </li>
 <li>
 Bias/fairness audits and data privacy
 </li>
 <li>
 Compliance with GDPR, ISO 42001, NIST AI RMF, and local banking regulations
 </li>
 <li>
 Secure prompt logging and audit trails
 
 
 </li>
 </ul>
 Products &amp; Strategy
 
 
 <ul>
 <li>
 Translating business problems into AI use cases
 </li>
 <li>
 Roadmapping and budget planning
 </li>
 <li>
 KPI design (accuracy, user satisfaction, automation ROI)
 </li>
 <li>
 Vendor management (OpenAI, Anthropic, AWS, etc.)
 </li>
 <li>
 Change management and user adoption
 
 
 </li>
 </ul>
 Skills: ai,design,nlp,data
</div>

Data Scientist (Core AI / NLP Engineering)

VAM SYSTEMS

<div>Job Description 
VAM Systems is currently looking for Data Scientists - Banking for our Bahrain operations with the following skillsets and terms &amp; conditions:
Years of Experience: 7 &ndash; 10 years
Qualification
Bachelor&rsquo;s Degree in Computer Science / Engineering 
Preferably BE Computer Science &amp; Engineering
Professional Training Required: Machine Learning, Deep Learning, MLOps, AI in Financial Services. 
Professional Qualification Required: Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable. 
Professional Certifications Required: TensorFlow Developer Certificate, AWS Certified Machine Learning.
Must-Have:<ul><li>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</li><li>Several years of ML experience with implemented use cases.</li><li>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</li></ul>
Experience required:
Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms. 
Experience with model evaluation and performance metrics.
Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering. 
Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management. 
Ability to communicate insights and build explainable AI models. 
 
 
Core AI / NLP Engineering<ul><li>Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)</li><li>LLM fine-tuning (LoRA, PEFT, prompt tuning)</li><li>Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)</li><li>Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)</li><li>Knowledge of embeddings, tokenization, and transformer architecture</li><li>Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch</li><li>Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)</li></ul>
 
Software Engineering &amp; Backend Integration<ul><li>RESTful and GraphQL APIs, webhooks</li><li>Containerization and deployment (Docker, Kubernetes, CI/CD)</li><li>Authentication and user/session management</li><li>Data pipelines and microservices</li><li>Knowledge of frameworks like FastAPI, Flask, NestJS, or Express</li><li>Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)</li></ul>
Agent Orchestration &amp; Tooling
<ul><li>LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks</li><li>Task-decomposition and reasoning chains</li><li>Function calling, tool use, and API chaining</li><li>Memory design (short-term vs long-term)</li><li>Context management and grounding strategies.</li></ul>
Joining time frame: (15 - 30 days)</div>

Data Scientists - Banking

DAMANA

<div>
 
 At Damana Insurance in Bahrain, we are currently recruiting for a System Analyst.
 
 
 
 
 
 As a Business System Analyst specializing in the insurance industry, you will be responsible for analyzing complex business processes, identifying areas for digital optimization, and collaborating with cross-functional teams to implement innovative solutions. Your role is pivotal in enhancing operational efficiency, customer experiences, and overall business success in the insurance and broking domain
 
 
 
 
 
 
 
 Main Responsibilities.
 
 
 
 
 
 
 
 
 1. Requirement Elicitation &amp; Documentation
 
 
 <ul>
 <li>
 Collaborate with insurance and broking stakeholders to gather, analyse, and document business requirements.
 </li>
 <li>
 Translate business needs into clear, detailed digital project specifications.
 </li>
 <li>
 Perform in-depth analysis of existing processes, systems, and pain points.
 </li>
 <li>
 Create BPMN workflows, identify process gaps, and propose innovative, scalable solutions.
 </li>
 </ul>
 
 
 
 
 
 2. Solution Design &amp; Development
 
 
 <ul>
 <li>
 Work closely with IT and development teams to design digital solutions tailored for the insurance and broking domain.
 </li>
 <li>
 Define functional specifications and produce BRDs, Functional Specification Documents, and Integration Documents.
 </li>
 <li>
 Ensure all solution designs comply with relevant insurance industry regulations and technical standards.
 </li>
 <li>
 Incorporate AI-driven enhancements into solution design where beneficial (e.g., automated classification, claim triage, fraud risk prediction, document understanding).
 </li>
 </ul>
 
 
 
 
 
 3. Development &amp; Technical Expertise
 
 
 <ul>
 <li>
 Proficient in
 
 Java
 
 and
 
 MongoDB
 
 for application and data development.
 </li>
 <li>
 Skilled in
 
 API integration technologies
 
 with strong hands-on experience using
 
 Postman
 
 .
 </li>
 <li>
 Possess conceptual (and practical where possible) understanding of
 
 no-code/low-code platforms
 
 .
 </li>
 <li>
 Document and design no-code solutions, translating business use cases into implementable no-code workflows.
 </li>
 <li>
 Basic understanding of AI/ML concepts such as classification models, NLP, embeddings, and prompt engineering for insurance use cases.
 </li>
 </ul>
 
 
 
 
 
 4. BI &amp; Reporting
 
 
 <ul>
 <li>
 Collaborate with data teams to define reporting requirements for underwriting, claims, broking operations, and financial KPIs.
 </li>
 <li>
 Work with BI tools (e.g., Power BI, Tableau, Looker) to design dashboards that visualize performance, trends, and operational insights.
 </li>
 <li>
 Translate raw data into clear, actionable reports for senior management and business teams.
 </li>
 <li>
 Ensure data accuracy, consistency, and alignment between operational systems and the reporting layer.
 </li>
 </ul>
 
 
 
 
 
 5. Project Management
 
 
 <ul>
 <li>
 Demonstrate full commitment to project timelines and deliverables
 </li>
 <li>
 Ensure projects are delivered on schedule.
 </li>
 </ul>
 
 
 
 
 
 6. Enterprise Architecture Alignment
 
 
 <ul>
 <li>
 Ensure all digital solutions are aligned with the enterprise architecture framework and internal standards.
 </li>
 <li>
 Continuously update related assets (business processes, architecture diagrams, data flows, system inventories) in
 
 iServer
 
 or equivalent EA tools.
 </li>
 <li>
 Facilitate change management efforts to ensure architectural artifacts remain accurate and up to date.
 </li>
 </ul>
 
 
 
 
 Education and qualification
 
 <ul>
 <li>
 Bachelor's degree in Computer Engineering.
 </li>
 <li>
 Proven experience as a Business Analyst in the insurance and broking sector
 </li>
 </ul>
 
 
</div>

System Analyst

Confidential

<figure class="table"><table><tbody><tr><td>Job Description:&nbsp;<ul><li>Build, deploy, and operate production AI systems and services.</li><li>Design and implement RAG pipelines across structured and unstructured data.</li><li>Develop AI-powered chatbots and automation workflows.</li><li>Integrate AI solutions with internal platforms, external data sources, and client systems.</li><li>Assist in fine-tuning LLMs and optimizing model performance.</li><li>Design data ingestion pipelines, including document processing and web data extraction.</li><li>Monitor AI systems and continuously optimize performance, reliability, and cost.</li><li>Collaborate with engineering, product, and operations teams to translate business requirements into AI solutions.</li><li>Ensure all AI systems comply with security, privacy, and reliability standards.</li></ul>&nbsp;Educational, Skills, and Experience:&nbsp;<ul><li>Bachelor’s degree in computer science, Engineering, Artificial Intelligence, or a related field.</li><li>3–5 years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong problem-solving and analytical abilities.</li><li>Ability to translate business requirements into scalable technical solutions.</li></ul>&nbsp;Technical Skills:&nbsp;<ul><li>Advanced Python development and API integration.</li><li>Experience working with Large Language Models (LLMs).</li><li>Design and implementation of Retrieval-Augmented Generation (RAG) systems.</li><li>Vector databases, embeddings, and search architectures.</li><li>AI model optimization, evaluation, and performance monitoring.</li><li>Data ingestion pipelines and document processing systems.</li><li>Familiarity with fine-tuning techniques and open-source LLMs.</li><li>Understanding of AI security, privacy, and cost optimization strategies.</li></ul>&nbsp;Additional Eligibility Qualifications&nbsp;<ul><li>Ability to work independently and as part of a team.</li><li>Strong organizational and time management skills.</li><li>Willingness to continuously learn and adapt.</li><li>Ability to handle multiple projects in a fast-paced environment.</li><li>Strong sense of responsibility and ownership of deliverables.</li></ul></td></tr></tbody></table></figure>

AI Engineer

<div>Job Description 
VAM Systems is currently looking for AI/ML Specialists (Data Scientists/ ML Engineer) (On-Site) for our Bahrain operations with the following skillsets and terms &amp; conditions:
Years of Experience: 7 &ndash; 10 years
Qualification
Bachelor&rsquo;s Degree in Computer Science / Engineering 
Preferably BE Computer Science &amp; Engineering
Professional Training Required: Machine Learning, Deep Learning, MLOps, AI in Financial Services. 
Professional Qualification Required: Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable. 
Professional Certifications Required: TensorFlow Developer Certificate, AWS Certified Machine Learning.
Must-Have:<ul><li>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</li><li>Several years of ML experience with implemented use cases.</li><li>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</li></ul>
Experience required:
Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms. 
Experience with model evaluation and performance metrics.
Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering. 
Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management. 
Ability to communicate insights and build explainable AI models. 
Joining time frame: (15 - 30 days)</div>

AI/ML Specialists (Data Scientists/ ML Engineer)

nineDots.io

<div>
 
 
 Full-Stack Engineer (Performance and Service Monitoring)
 
 
 
 Real-Time Systems - Reliability Engineering - AI Platform
 
 
 
 
 
 
 
 Join a fast-growing AI company helping global enterprises accelerate the adoption of applied AI. You will design and develop monitoring and performance systems that keep a high-usage platform stable, fast, and secure across demanding environments.
 
 
 
 
 
 
 
 
 The Role
 
 
 
 As a Full-Stack Engineer focused on performance and service monitoring, you will design, build, and evolve the systems that ensure uptime, reliability, and real-time responsiveness across the platform. You will work across engineering, product, and compliance to improve observability, build dashboards, and maintain high availability.
 
 
 
 
 
 
 
 This is a hands-on engineering role that blends full-stack development with real-time monitoring, performance optimisation, and reliable system behaviour.
 
 
 
 
 
 
 
 
 What You Will Be Doing
 
 
 <ul>
 <li>
 Designing and implementing performance monitoring systems across the platform.
 </li>
 <li>
 Building dashboards, alerting pipelines, and observability tooling.
 </li>
 <li>
 Developing performant frontend features using Next.js and React.
 </li>
 <li>
 Creating backend APIs and microservices using Node.js and Python.
 </li>
 <li>
 Implementing WebSocket and event-driven architectures for real-time data flow.
 </li>
 <li>
 Ensuring monitoring systems align with SOC 2, ISO 27001, and ISO 27018.
 </li>
 <li>
 Integrating notifications into tools like Slack and Microsoft Teams.
 </li>
 <li>
 Continuously improving system reliability, latency, and uptime.
 </li>
 </ul>
 
 
 
 
 
 
 
 What You Need To Succeed
 
 
 <ul>
 <li>
 Strong experience in full-stack engineering.
 </li>
 <li>
 Proficiency with Next.js, React, Node.js, and Python.
 </li>
 <li>
 Experience with monitoring, observability, or real-time systems.
 </li>
 <li>
 Familiarity with CloudWatch, Prometheus, Grafana, or similar stacks.
 </li>
 <li>
 Experience with WebSockets and event-driven architectures.
 </li>
 <li>
 Strong understanding of secure coding and compliance alignment.
 </li>
 <li>
 Comfortable working across cloud environments and CI/CD pipelines.
 </li>
 <li>
 Strong problem-solving skills with a focus on reliability and performance.
 </li>
 </ul>
 
 
 
 
 
 
 
 What&rsquo;s In It For You
 
 
 <ul>
 <li>
 Ownership of critical monitoring and reliability systems across a global AI platform.
 </li>
 <li>
 Modern tooling and real-time engineering challenges.
 </li>
 <li>
 Competitive salary and flexible work setup.
 </li>
 <li>
 Work with a fast-growing AI company supporting major enterprises.
 </li>
 <li>
 Equity potential and an environment that values technical excellence.
 </li>
 </ul>
 
 
 
 
 
 
 
 Next Steps
 
 
 
 If this role matches the type of engineering challenges you want to work on, we would like to hear from you. Send your CV or reach out in confidence for more details.
 
</div>

Full-Stack Engineer (Performance and Service Monitoring)

Canonical

<div>
 The role of a Growth Engineer at Canonical
 
 
 Canonical has provided developers with open source since 2004, helping them build innovations such as public cloud, machine learning, robotics or blockchain. Marketing at Canonical means being at the forefront of technology adoption, for our customers and for our own martech stack. We are looking for an experienced
 
 Growth Engineer
 
 to join our team and take ownership of our marketing technology stack, data architecture, and infrastructure. This role is critical for designing and scaling the systems that power marketing automation, lifecycle marketing, and data-driven growth initiatives.
 
 
 The ideal candidate will be passionate about technology, data, and the use of technology in marketing. You will thrive in an environment that emphasizes ownership, collaboration, learning, and a drive to continually improve. If you love to solve complex problems, get hands-on with cutting-edge tools, and build the automated systems that fuel a global business, we want to talk with you.
 
 
 This role sits in the Marketing team reporting to the Growth Engineering Manager.
 
 
 
 Location:
 
 This role will be based remotely in the EMEA region.
 
 
 What your day will look like
 
 
 <ul>
 <li>
 Design, build, and maintain our core data infrastructure and martech stack to support marketing and sales goals.
 </li>
 <li>
 Develop and optimize robust data pipelines, automations, and integrations between our CRM, marketing platforms, and data warehouse.
 </li>
 <li>
 Architect and manage APIs for seamless system integration and data flow across the entire stack.
 </li>
 <li>
 Collaborate with marketing, sales, and product teams to understand their needs and architect technical solutions.
 </li>
 <li>
 Implement and champion software engineering best practices, including clean code, CI/CD, automated testing, and version control.
 </li>
 <li>
 Explore and integrate cutting-edge tools to enhance our data capabilities and operational efficiency.
 </li>
 <li>
 Support marketing team members with strategic expertise, setting up and monitoring automations
 </li>
 <li>
 Build on automation and AI to improve lead management
 </li>
 <li>
 Develop Canonical's martech stack to industry leading standard
 
 
 </li>
 </ul>
 What we are looking for in you?
 
 
 <ul>
 <li>
 
 System Design:
 
 Expertise in system design, particularly in the data world, with a strong understanding of networking, proxies, and data ingress/egress patterns.
 </li>
 <li>
 
 Cloud &amp; Databases:
 
 Proficiency with cloud data warehousing (e.g., BigQuery), relational databases (e.g., Postgres), and object stores (e.g., S3). Knowledge of Docker, Kubernetes, and data stores like Redis is a plus.
 </li>
 <li>
 
 API Architecture:
 
 Deep knowledge of API architecture and design, with a primary focus on REST. Experience with GraphQL is beneficial.
 </li>
 <li>
 
 Programming:
 
 Senior-level knowledge of Python (OOP, APIs, asyncio, scientific libraries) and SQL (experience with tools like Trino and dbt is highly valued).
 </li>
 <li>
 
 Web Technologies:
 
 A solid understanding of web application backend-frontend processes. Working knowledge of JavaScript is required; experience with React is a nice-to-have.
 </li>
 <li>
 
 Engineering Best Practices:
 
 A commitment to writing clean, maintainable code, with experience in CI/CD, automated testing, and version control (Git).
 </li>
 <li>
 
 Mindset:
 
 A curious and collaborative problem-solver with a growth mindset and a keen interest in the commercial domains of marketing and sales. Plus, exceptional interpersonal skills and aptitude for forging trusting relationships across diverse, cross-functional teams
 
 
 </li>
 </ul>
 What we offer you
 
 
 Your base pay will depend on various factors including your geographical location, level of experience, knowledge and skills. In addition to the benefits above, certain roles are also eligible for additional benefits and rewards including annual bonuses and sales incentives based on revenue or utilisation. Our compensation philosophy is to ensure equity right across our global workforce.
 
 
 In addition to a competitive base pay, we provide all team members with additional benefits, which reflect our values and ideals. Please note that additional benefits may apply depending on the work location and, for more information on these, you can ask in the later stages of the recruitment process.
 
 
 🏠Fully remote working environment - we've been working remotely since 2004!
 
 
 📚Personal learning and development budget of 2,000USD per annum
 
 
 💰Annual compensation review
 
 
 🏆Recognition rewards
 
 
 🏝 Annual holiday leave
 
 
 👶Parental Leave
 
 
 🧑&zwj;💼Employee Assistance Programme
 
 
 🧳Opportunity to travel to new locations to meet colleagues at 'sprints'
 
 
 ✈️Priority Pass for travel and travel upgrades for long haul company events
 
 
 
 About Canonical
 
 
 
 Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do.
 
 
 Canonical has been a remote-first company since its inception in 2004. Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business.
 
 
 Canonical is an equal opportunity employer
 
 
 We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.
 
 
</div>

Growth Engineer

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