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ai data scientist

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: AI Data Scientist (Offshore)</h2>
Duration: 6 Months (Extendable) 
Experience: 6&ndash;8 Years 
Location: Offshore (Remote) 
Industry: Multi-Industry (with focus on Financial Sector) 
Employment Type: Contract (6 Months - Higher possiblity for extension)<h3 class="jobSectionHeader">
Job Summary</h3>
We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain. The ideal candidate will have strong proficiency in Python, SQL, and Google Cloud Platform (GCP) tools &mdash; leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.
This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3><ul><li>
Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.</li><li>
Work closely with business stakeholders&mdash;especially in the financial sector&mdash;to translate complex problems into AI-driven solutions.</li><li>
Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.</li><li>
Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.</li><li>
Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.</li><li>
Visualize insights and performance metrics using Looker and other BI tools.</li><li>
Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.</li><li>
Evaluate model performance and refine algorithms for improved accuracy and business impact.</li></ul><h3 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h3><ul><li>
5&ndash;8 years of professional experience in data science, AI/ML, and analytics roles.</li><li>
Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.</li><li>
Hands-on experience with GCP ecosystem, including:<ul><li>
BigQuery (data querying and transformation)</li><li>
Vertex AI (model training, tuning, deployment)</li><li>
Dataflow / Dataproc (data processing pipelines)</li><li>
Pub/Sub (event-driven data streaming)</li><li>
GCS (Google Cloud Storage) and Looker (visualization and reporting)</li></ul></li><li>
Strong knowledge of MLOps automation and continuous deployment best practices.</li><li>
Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).</li><li>
Strong understanding of statistical modeling, feature engineering, and model performance evaluation.</li><li>
Excellent problem-solving and communication skills with ability to work in multi-industry environments.</li></ul><h3 class="jobSectionHeader"> 
Preferred Qualifications</h3><ul><li>
Experience in multi-cloud or hybrid environments.</li><li>
Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).</li><li>
Exposure to deep learning frameworks (TensorFlow, PyTorch).</li><li>
Experience in time-series forecasting, credit modeling, or financial risk analytics.</li></ul>
RE2l5yQYY6</div>

AI Data Scientist

Datamatics Technologies

<div>
 
 Job Title:
 
 AI Data Scientist (Offshore)
 
 
 
 Duration:
 
 6 Months (Extendable)
 
 
 Experience:
 
 &nbsp;6&ndash;8 Years
 
 
 Location:
 
 Offshore (Remote)
 
 
 Industry:
 
 Multi-Industry (with focus on Financial Sector)
 
 
 Employment Type:
 
 Contract (6 Months - Higher possiblity for extension)
 
 
 
 Job Summary
 
 
 We are seeking a highly skilled
 
 AI Data Scientist
 
 with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the
 
 financial services domain
 
 . The ideal candidate will have strong proficiency in
 
 Python, SQL
 
 , and
 
 Google Cloud Platform (GCP)
 
 tools &mdash; leveraging platforms like
 
 BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker
 
 to deliver scalable and automated AI solutions.
 
 
 This is an exciting
 
 6-month contract role (with potential extension)
 
 focused on developing
 
 descriptive, predictive, and prescriptive models
 
 and deploying them in production using
 
 MLOps best practices
 
 .
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Design and develop
 
 data science and machine learning models
 
 across descriptive, predictive, and prescriptive analytics.
 
 </li>
 <li>
 
 Work closely with business stakeholders&mdash;especially in the
 
 financial sector
 
 &mdash;to translate complex problems into AI-driven solutions.
 
 </li>
 <li>
 
 Develop and automate
 
 end-to-end ML pipelines
 
 on
 
 GCP
 
 using Vertex AI, Dataflow, Pub/Sub, and Dataproc.
 
 </li>
 <li>
 
 Implement
 
 MLOps
 
 frameworks for continuous integration, deployment, and monitoring of machine learning models.
 
 </li>
 <li>
 
 Analyze large datasets using
 
 BigQuery
 
 and other GCP-native tools for data transformation, feature engineering, and model training.
 
 </li>
 <li>
 
 Visualize insights and performance metrics using
 
 Looker
 
 and other BI tools.
 
 </li>
 <li>
 
 Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.
 
 </li>
 <li>
 
 Evaluate model performance and refine algorithms for improved accuracy and business impact.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 
 
 5&ndash;8 years
 
 of professional experience in
 
 data science, AI/ML
 
 , and analytics roles.
 
 </li>
 <li>
 
 Proven expertise in
 
 Python
 
 (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and
 
 SQL
 
 for data analysis and model development.
 
 </li>
 <li>
 
 Hands-on experience with
 
 GCP ecosystem
 
 , including:
 
 <ul>
 <li>
 
 
 BigQuery
 
 (data querying and transformation)
 
 </li>
 <li>
 
 
 Vertex AI
 
 (model training, tuning, deployment)
 
 </li>
 <li>
 
 
 Dataflow / Dataproc
 
 (data processing pipelines)
 
 </li>
 <li>
 
 
 Pub/Sub
 
 (event-driven data streaming)
 
 </li>
 <li>
 
 
 GCS (Google Cloud Storage)
 
 and
 
 Looker
 
 (visualization and reporting)
 
 </li>
 </ul>
 </li>
 <li>
 
 Strong knowledge of
 
 MLOps automation
 
 and continuous deployment best practices.
 
 </li>
 <li>
 
 Experience developing models in
 
 financial services
 
 (risk scoring, fraud detection, customer analytics, forecasting, etc.).
 
 </li>
 <li>
 
 Strong understanding of
 
 statistical modeling
 
 ,
 
 feature engineering
 
 , and
 
 model performance evaluation
 
 .
 
 </li>
 <li>
 
 Excellent problem-solving and communication skills with ability to work in multi-industry environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 
 Experience in
 
 multi-cloud
 
 or hybrid environments.
 
 </li>
 <li>
 
 Knowledge of
 
 CI/CD pipelines
 
 for ML (GitHub Actions, Jenkins, or Cloud Build).
 
 </li>
 <li>
 
 Exposure to
 
 deep learning frameworks
 
 (TensorFlow, PyTorch).
 
 </li>
 <li>
 
 Experience in
 
 time-series forecasting
 
 ,
 
 credit modeling
 
 , or
 
 financial risk analytics
 
 .
 
 </li>
 </ul>
</div>

Osol

<div>
 
 
 Company Overview
 
 
 
 Osol Tech Pvt. Ltd. is a fast-growing software development and professional services company, pioneering AI/ML-driven innovation across industries. We empower organizations in manufacturing, healthcare, retail, and e-commerce to make smarter, data-driven decisions through advanced analytics, predictive modeling, and AI solutions. Our culture fosters continuous learning, collaboration, and innovation at scale.
 
 
 
 
 
 
 Job Summary
 
 
 
 We are seeking a Senior Data Scientist to lead the design and implementation of advanced analytics and data science solutions. This role requires a strong foundation in statistics, machine learning, data engineering, and domain-driven problem solving.
 
 
 
 
 
 The ideal candidate will have experience building end-to-end data science solutions &mdash; from exploratory data analysis and feature engineering to production-ready models and business insights. You will collaborate closely with engineers, analysts, and business stakeholders to drive measurable outcomes.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build, and evaluate predictive and prescriptive models (regression, classification, forecasting, clustering, recommendation systems).
 </li>
 <li>
 Apply advanced ML methods (gradient boosting, ensemble models, transformers for tabular/text, probabilistic models).
 </li>
 <li>
 Conduct A/B tests and causal inference to measure business impact.
 </li>
 <li>
 Perform exploratory data analysis (EDA) using statistical and visualization tools.
 </li>
 <li>
 Translate data findings into actionable insights with clear storytelling for non-technical audiences.
 </li>
 <li>
 Build dashboards and reports to support decision-making.
 </li>
 <li>
 Work with SQL, Spark, Dask, or BigQuery to process and transform large datasets.
 </li>
 <li>
 Collaborate with data engineers to ensure high-quality, reliable data pipelines.
 </li>
 <li>
 Apply feature engineering, data augmentation, and missing data handling strategies.
 </li>
 <li>
 Contribute to model deployment using MLflow, SageMaker, Vertex AI, or Azure ML.
 </li>
 <li>
 Support model monitoring and retraining strategies.
 </li>
 <li>
 Use Python (Pandas, NumPy, Scikit-learn, Statsmodels, PyTorch/TensorFlow), R, SQL, and Jupyter for analysis and modeling.
 </li>
 <li>
 Use visualization &amp; BI tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau, Looker).
 </li>
 <li>
 Track experiments with MLflow, DVC, or Weights &amp; Biases.
 </li>
 <li>
 Partner with product managers and business teams to frame problems and define success metrics.
 </li>
 <li>
 Mentor junior data scientists and analysts.
 </li>
 <li>
 Champion data-driven decision-making across the organization.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications &amp; Skills
 
 
 <ul>
 <li>
 Strong programming skills in Python and SQL; familiarity with R or Julia is a plus.
 </li>
 <li>
 Solid foundation in statistics, probability, linear algebra, and hypothesis testing.
 </li>
 <li>
 Experience with machine learning techniques (supervised/unsupervised learning, ensembles, time series).
 </li>
 <li>
 Proficiency with data visualization and ability to communicate insights effectively.
 </li>
 <li>
 Hands-on experience with big data tools (Spark, Dask, BigQuery).
 </li>
 <li>
 Cloud experience with AWS, GCP, or Azure for data science workflows.
 </li>
 <li>
 Familiarity with version control (Git), experiment tracking, and reproducible workflows.
 </li>
 <li>
 Excellent communication, collaboration, and problem-solving skills.
 </li>
 <li>
 Proven ability to mentor junior engineers and lead initiatives.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Domain expertise in manufacturing, healthcare, retail, or e-commerce applications.
 </li>
 <li>
 Experience with NLP or computer vision applied to data-rich use cases.
 </li>
 <li>
 Hands-on experience with causal inference, Bayesian methods, or reinforcement learning for experimentation.
 </li>
 <li>
 Prior open-source contributions, publications, or patents.
 </li>
 <li>
 Experience with BI/analytics strategy and executive-level presentations.
 </li>
 </ul>
 
 
 
 
 
 Education &amp; Experience
 
 
 
 &bull; Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
 
 
 &bull; PhD or strong research experience is a plus, but not required.
 
 
 &bull; 5&ndash;7+ years of professional experience in data science or advanced analytics, with evidence of driving business impact.
 
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 High-impact data science projects that solve real-world problems.
 </li>
 <li>
 Continuous learning opportunities with cloud credits, courses, and conference sponsorships.
 </li>
 <li>
 Competitive salary, benefits, and performance-based incentives.
 </li>
 <li>
 Flexible hybrid/remote working environment.
 </li>
 <li>
 A culture of collaboration, innovation, and knowledge sharing.
 </li>
 </ul>
 
 
 
</div>

Senior Data Scientist

ibex

<div>
 We are looking for a proactive and analytical
 
 Data Scientist
 
 to join our growing team. The ideal candidate will be deeply passionate about working with data, possess a strong foundation in statistical analysis and machine learning, and demonstrate the ability to derive actionable insights from complex datasets. This role requires experience in data wrangling, exploratory data analysis (EDA), and hands-on implementation of data science techniques, including Natural Language Processing (NLP).
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Collect, clean, and organize structured and unstructured data from diverse sources.
 </li>
 <li>
 Ensure data accuracy, consistency, and readiness for analysis.
 </li>
 <li>
 Perform thorough EDA to understand data distributions, relationships, and anomalies.
 </li>
 <li>
 Use visualization tools (e.g., Matplotlib, Seaborn, Pandas) to communicate findings.
 </li>
 <li>
 Work closely with business teams to identify trends and patterns that guide decisions.
 </li>
 <li>
 Handle missing data, outliers, and normalization techniques effectively.
 </li>
 <li>
 Transform raw data into features suitable for modeling and insights.
 </li>
 <li>
 Automate and optimize data preparation pipelines.
 </li>
 <li>
 Develop NLP pipelines for text classification, sentiment analysis, named entity recognition, and more.
 </li>
 <li>
 Work with tools such as NLTK, Hugging Face Transformers, and BERT-based models.
 </li>
 <li>
 Analyze and process unstructured text data for business use cases.
 </li>
 <li>
 Translate complex data problems into clear, actionable insights.
 </li>
 <li>
 Proactively identify opportunities for data-driven improvements across departments.
 </li>
 <li>
 Conduct root cause analysis and support hypothesis-driven investigations.
 </li>
 <li>
 Work closely with cross-functional teams including data engineers, analysts, and product stakeholders.
 </li>
 <li>
 Exhibit a high level of accountability, ownership, and willingness to support teammates.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, or a related field.
 </li>
 <li>
 2&ndash;3 years of experience in a data science role.
 </li>
 <li>
 Proficiency in Python (NumPy, Pandas, Scikit-learn), SQL and MongoDB
 </li>
 <li>
 Hands-on experience with NLP frameworks such as NLTK, or Hugging Face.
 </li>
 <li>
 Solid understanding of machine learning algorithms and data modeling techniques.
 </li>
 <li>
 Strong data visualization and storytelling skills.
 </li>
 <li>
 Excellent problem-solving and critical thinking abilities.
 </li>
 <li>
 Strong communication skills and a collaborative mindset.
 </li>
 </ul>
</div>

Data Scientist, Tech

CodeNinja

About the Company: 
CodeNinja is a global AI and software engineering firm that helps organizations build, scale, and operate intelligent digital solutions. With a strong focus on AI, data platforms, and cloud-native systems, CodeNinja partners with enterprises to deliver high-impact technology outcomes across industries. The company operates across multiple regions, working with global clients to solve complex business problems through innovation and engineering excellence.
 
Role Overview: 
CodeNinja is seeking a Business Analyst to support presales and engineering teams through effective requirements discovery, analysis, and documentation. The role focuses on translating prospective client needs into clear functional and technical requirements that enable proposal development, solution design, and delivery — including AI and data-driven solutions.
 
Key Responsibilities: 
Presales & Requirements Discovery: 
<ul>
<li>Lead requirements discovery sessions with prospective clients.</li>
<li>Conduct workshops and interviews to identify business goals, functional and non-functional requirements, data and AI needs, assumptions, risks, and dependencies.</li>
<li>Document requirements clearly to support solutioning, estimation, and AI feasibility.</li>
</ul>
Documentation & Engineering Enablement: 
<ul>
<li>Convert requirements into functional specifications, user stories, acceptance criteria, and high-level process/data flows.</li>
<li>Maintain engineering-ready documentation and clarify requirements with engineering and AI teams.</li>
</ul>
Presales & Proposal Support: 
<ul>
<li>Support proposal development, RFP/RFI responses, scope definition, and assumptions.</li>
<li>Ensure proposals are based on validated requirements, including AI scope and data dependencies.</li>
</ul>
POC / Prototype Support: 
<ul>
<li>Support AI and digital POCs by defining scope, success criteria, and validating AI use cases (e.g., RAG feasibility, agent behavior).</li>
<li>Prepare client-facing POC documentation.</li>
</ul>
Jira & Backlog Management: 
<ul>
<li>Create and maintain Jira epics, user stories, and tasks.</li>
<li>Ensure end-to-end traceability from discovery to development.</li>
</ul>
Cross-Functional Collaboration: 
<ul>
<li>Act as a liaison between presales, engineering, AI/data teams, and clients.</li>
<li>Ensure smooth handover from presales to delivery.</li>
</ul>
Requirements: 
Required Skills & Experience: 
<ul>
<li>5+ years of experience in business analysis, preferably in presales or consulting.</li>
<li>Strong expertise in requirements elicitation, analysis, and documentation.</li>
<li>Experience supporting presales activities, proposals, or RFPs.</li>
<li>Understanding of SDLC, APIs, system integrations, databases, and cloud platforms (AWS/Azure/GCP).</li>
<li>Foundational understanding of AI solutions, including ML concepts, Agentic AI, and RAG patterns.</li>
<li>Hands-on experience with Jira and structured documentation (BRDs, FRDs, user stories).</li>
<li>Strong communication and stakeholder management skills.</li>
</ul>
Why Join CodeNinja: 
<ul>
<li>Be a key contributor to AI-driven and digital presales engagements.</li>
<li>Collaborate with solution architects, AI engineers, data teams, and sales leaders.</li>
<li>Gain exposure to modern AI platforms, data systems, and cloud technologies.</li>
<li>Clear growth opportunities into Senior Business Analyst roles.</li>
</ul>
Disclaimer
 CodeNinja is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, and performance. Female and minorities are strongly encouraged and preferred to apply for the role.

Business Analyst - Pre Sales

Cloudelligent

<div>Position Title: Sr. AWS AI Engineer 
Location: Lahore 
Job Timings: 6pm-3am Pakistan Time (PKT) 
 
About Cloudelligent 
 
Cloudelligent is Cloud-native consultancy and AWS Advanced consulting partner! We specialize in providing bespoke cloud solutions to startups and SMBs. Being a next-gen cloud service provider, Cloudelligent helps businesses to make the most out of their cloud investment. We have an international footprint with a diverse team of domain experts, and we are customer obsessed. 
 
Job Objective 
 
As a Sr. AWS AI Engineer at Cloudelligent, you will drive the development of innovative artificial intelligence solutions. This role emphasizes the implementation, optimization, and deployment of AI models while collaborating with cross-functional teams to enhance our products and services. The ideal candidate will possess a strong foundation in both machine learning and deep learning. Additionally, this role will lead and manage a team of AI engineers, guiding their growth and ensuring the successful delivery of AI-driven solutions. 
 
Responsibilities:<ul><li>
Implement and fine-tune pre-trained AI models tailored to meet specific industry needs.</li><li>
Utilize cloud-based AI services, particularly AWS Bedrock, Amazon SageMaker, Amazon Rekognition, and OpenAI, to streamline development and deployment processes.</li><li>
Leverage AWS data services, including Amazon Athena, Amazon Redshift, OpenSearch, Kendra and AWS Glue, for efficient data processing and analysis.</li><li>
Optimize AI models for performance, accuracy, and efficiency, ensuring they meet real-world requirements.</li><li>
Apply techniques to reduce AI hallucination and enhance model reliability.</li><li>
Utilize Retrieval-Augmented Generation (RAG) techniques to improve AI response quality.</li><li>
Work with vector databases, specifically PostgreSQL with pgvector, for efficient similarity search and information retrieval in AI applications.</li><li>
Collaborate with cross-functional teams to seamlessly integrate AI capabilities into our products and services.</li><li>
Engage in prompt engineering to enhance model interaction and output quality.</li><li>
Stay updated on the latest trends and advancements in AI technologies, contributing to the adoption of new tools and techniques.</li></ul>
Requirements:<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Machine Learning, or a related field.</li><li>
5+ years of hands-on experience in AI/ML development with a strong focus on AWS-based AI services.
</li><li>Advanced proficiency in Python and expertise in AI/ML frameworks such as TensorFlow, PyTorch, or Keras.</li><li>
Extensive experience with AWS AI services, including Amazon SageMaker, AWS Bedrock, and integrating Azure OpenAI into cloud-based solutions.</li><li>
In-depth knowledge of AWS data services, including Amazon Athena, Amazon Redshift, AWS Glue, and their application in AI/ML pipelines.</li><li>
Expertise in Agentic Behavior in AI and deploying models using technologies like CrewAI, LangGraph, and Langchain.</li><li>
Experience with vector databases and similarity search techniques for scalable AI solutions.</li><li>
Understanding of AI/ML algorithms and architectures, including CNNs, RNNs, transformers, and experience building end-to-end solutions.</li><li>
Expertise in data preprocessing, feature engineering, and model evaluation at scale.</li><li>
Demonstrated ability to lead AI/ML projects and communicate complex ideas effectively to both technical and non-technical stakeholders.</li></ul>
Good to Have:<ul><li>
Experience with machine learning frameworks and libraries like TensorFlow, PyTorch, or Scikit-learn.</li><li>
Knowledge of big data technologies such as Apache Spark or Hadoop.</li><li>
Familiarity with data visualization tools and techniques.</li></ul>
Highly Desirable:<ul><li>
Relevant certifications (e.g., AWS Certified Machine Learning &ndash; Specialty, AWS Certified AI Practitioner).</li></ul> 

YrFW1AObcG</div>

Sr. AWS AI Engineer

Skylinx Technologies

We are hiring an in-house AI Engineer to join our Lahore-based engineering team. This role focuses on building and deploying AI-driven features for our custom platform, including data intelligence, competitive alerts, and user-facing AI interfaces. You will work closely with backend and product teams and have direct ownership of AI integrations and deployments.Key Responsibilities<ul><li>Work with existing machine learning models and large language models (LLMs).</li><li>Deploy and manage AI/ML models on private cloud or self-hosted infrastructure.</li><li>Integrate third-party AI tools and APIs (e.g., Groq, OpenAI, Hugging Face, vector databases).</li><li>Build data pipelines by connecting AI models with relational and NoSQL databases.</li><li>Design and implement competitive alerts, insights, and notifications from structured and unstructured data.</li><li>Develop APIs and basic interfaces to expose AI capabilities within the platform.</li><li>Optimize inference performance, cost, and scalability.</li><li>Ensure data security and privacy in AI workflows.</li><li>Collaborate closely with in-house backend, frontend, and product teams.</li></ul>Required Skills &amp; Qualifications<ul><li>2+ years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong proficiency in Python.</li><li>Hands-on experience with machine learning models, LLMs, or inference pipelines.</li><li>Experience deploying models on private cloud, VPS, or on-prem infrastructure.</li><li>Familiarity with third-party AI platforms and tools (e.g., Groq, OpenAI, Anthropic).</li><li>Experience working with databases (MySQL, PostgreSQL, MongoDB, etc.).</li><li>Ability to build and consume REST APIs.</li><li>Basic experience with interfaces or dashboards for AI-powered features.</li><li>Strong problem-solving skills and ability to work in an on-site team environment.</li></ul>Nice to Have<ul><li>Experience with RAG (Retrieval-Augmented Generation) systems.</li><li>Knowledge of alerting systems, recommendation engines, or analytics dashboards.</li><li>Familiarity with Docker, Kubernetes, or MLOps workflows.</li><li>Experience in SaaS or data-driven platforms.</li><li>Frontend exposure (React, Vue, or similar).</li></ul>What We Offer<ul><li>On-site role in Lahore with a collaborative engineering team.</li><li>Opportunity to build production-grade AI systems.</li><li>Competitive salary</li><li>Long-term growth and learning opportunities.</li><li>Direct impact on core product features.</li></ul>How to ApplyPlease share:<ul><li>Your updated resume</li><li>GitHub or project links (if available)</li><li>Short summary of AI or ML projects you&rsquo;ve worked on</li></ul>Job Types: Full-time, Contract Contract length: 12 monthsWork Location: In person

AI Engineer (In-House)

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AI Data Scientist

AI Data Scientist

Senior Data Scientist

Data Scientist, Tech

Business Analyst - Pre Sales

Sr. AWS AI Engineer

AI Engineer (In-House)