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Confiz

<div>We are looking for a Principal Data Engineer, responsible for leading data engineering teams. He/she will provide guidance, mentorship, and technical expertise to team members, fostering a collaborative and innovative work environment. Collaboration is key for a Principal Data Engineer as he/she will work closely with stakeholders to define project requirements. Therefore, a commitment to collaborative problem solving, sophisticated design, and the creation of quality products is essential.
Responsibilities:
<ul><li>Collaborate with Big Data Solution Architects to design, prototype, implement, and optimize data ingestion pipelines so that data is shared effectively across various business systems.</li>
<li>Build &amp; maintain ETL/ELT Ingestion pipelines and analytics solutions using cloud technologies.</li>
<li>Ensure the design, code and procedural aspects of solution are production ready, in terms of operational, security and compliance standards.</li>
<li>Implement monitoring and logging solutions to ensure data pipelines run smoothly and issues are promptly identified.</li>
<li>Ensure all data processing complies with security policies and data protection regulations.</li>
<li>Takes the lead in ensuring that data is accurate, consistent, and reliable.</li>
<li>Participate in day-to-day project and production delivery status meetings, and provide technical support for faster resolution of issues.</li>
<li>Work with Stakeholders and Understand their Requirements</li>
</ul>
Qualifications
<ul><li>Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent work experience).</li>
<li>5+ years of overall experience in data engineering &amp; data warehousing domain focusing on building large scale data pipelines</li>
<li>3+ years' experience in Big Data Distributed systems such as Microsoft Fabric, Databricks, AWS EMR</li>
<li>Strong experience in developing data pipelines using PySpark and ETL tools like ADF, Talend</li>
<li>Proficiency in Python &amp; SQL</li>
<li>Solid understanding of data modelling, ETL processes, and best practices in data warehousing domain</li>
<li>Strong problems solving and critical thinking skills</li>
<li>Experience of writing effective and maintainable unit and integration tests for ingestion pipelines.</li>
<li>Working knowledge of CI/CD pipelines for deployments.</li>
<li>Working knowledge of using code version control repositories like Git.</li>
<li>Knowledge of designing, developing, and managing Kafka-based data pipelines</li>
<li>Knowledge of security best practices including encryption of sensitive data, encryption at rest and encryption in flight.</li>
</ul>
We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM), ISO 14001:2015 (EMS), ISO 45001:2018 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/</div>

Principal Data Engineer

<div>
 We seek an experienced Big Data expert to lead our Big Data platform's design, development, and maintenance. Collaborating with data engineers and Big Data Business Analysts across various platform layers, you'll demonstrate a commitment to collaborative problem-solving, sophisticated design, and delivering high-quality products.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Facilitate and lead the roadmap and enhancements for the enterprise Big Data platform.
 </li>
 <li>
 Lead Data Engineers, Business Analysts, and BI engineers to architect and deliver the solutions that fulfill the Business information needs.
 </li>
 <li>
 Ensure the design, code, and procedural aspects of the solution are production-ready, in terms of operational, security, and compliance standards.
 </li>
 <li>
 Participate in day-to-day project and production delivery status meetings, and provide technical support for faster resolution of issues.
 </li>
 <li>
 Yearning for continuous learning and training/mentoring future big data developers and architects.
 </li>
 <li>
 Design and implement scalable, near real-time data ingestion pipelines to enable low-latency data processing and analytics.
 </li>
 <li>
 Architect and optimize data streaming solutions to handle high-throughput, distributed systems while ensuring data consistency, reliability, and fault tolerance in near real-time workflows.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 14 years of experience in enterprise data architecture, integration, and analytics, with a proven track record of design and implementation of big data and analytics solutions in recent years.
 </li>
 <li>
 Experience in leading a team of Data Engineers and BI Developers.
 </li>
 <li>
 Bachelor&rsquo;s degree in computer science or relevant field from an accredited college or university; Master&rsquo;s degree from an accredited college or university preferred.
 </li>
 <li>
 Strong technical experience in the following:
 </li>
 <li>
 Big data stack and solutions, including cloud technologies.
 </li>
 <ul>
 <li>
 Data lake architecture, including data model design and implementation (incl. relational, dimensional, and No-SQL).
 </li>
 <li>
 Enterprise Application and Data Integration design and implementation (e.g. ETL, messaging, replication, and APIs).
 </li>
 <li>
 Telco Domain Experience
 </li>
 <li>
 Azure Solutions Architect Certification
 </li>
 <li>
 Azure Data Lake, Azure Data Factory, Databricks, Azure SQL, Apache NiFi, Azure Synapse, Power BI
 </li>
 </ul>
 <li>
 Awareness of Data management best practices (e.g. data quality, metadata management, data lineage).
 </li>
 <li>
 Awareness of Machine Learning techniques is nice to have
 </li>
 <li>
 Willingness to travel to UK (25% travelling might be required)
 
 </li>
 </ul>
 We have an amazing team of 700+ individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.
 
 
 What makes Confiz stand out is our focus on processes and culture. Confiz is
 
 ISO 9001:2015
 
 (QMS),
 
 ISO 27001:2022
 
 (ISMS),
 
 ISO 20000-1:2018
 
 (ITSM),
 
 ISO 14001:2015
 
 (EMS),
 
 ISO 45001:2018
 
 (OHSMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.
 
 
 People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.
 
 
 To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/
</div>

Big Data Architect

MOBIZ

<div>About Mobiz

Mobiz is an information technology firm, and we do three things exceptionally well: cloud and network automation, digital transformation, and data protection. Double-digit growth year-over-year has driven us to grow our team and ensure we stay ahead of the curve. 
What Can You Expect?

Every day at Mobiz we work with a deep sense of purpose. We continuously innovate. Our mission is to empower our clients to do more through transformation. You&rsquo;ll work in a collaborative environment alongside highly talented people that improve client operations and exceed expectations. We strive to simplify technology challenges, and no less. 


Who Are We Looking For?

We are looking for a skilled and motivated Data Engineer to join our growing data team. In this role, you will be responsible for designing, building, and operating scalable, secure, and high-performing data solutions that enable analytics, reporting, and data-driven decision-making across the organization. You will collaborate closely with cross-functional teams and leverage modern cloud technologies to transform raw data into trusted, accessible insights. 


Key Responsibilities
<ul>
<li>Design, build, test, deploy, and maintain robust data pipelines using Databricks, Azure Data Factory, and Microsoft Fabric, supporting both batch and streaming workloads.</li>
<li>Ingest, integrate, and harmonize data from multiple cloud and on-premises sources to deliver a unified, reliable, and trusted data view for analytics and reporting.</li>
<li>Use Python and SQL to clean, transform, validate, and model data to meet business, reporting, and analytical requirements.</li>
<li>Contribute to data architecture and platform design decisions, ensuring solutions are scalable, secure, cost-effective, and aligned with long-term business and technical strategy.</li>
<li>Build and maintain metadata-driven pipelines that gracefully adapt to schema changes, new data sources, and evolving ingestion patterns.</li>
<li>Proactively identify data quality issues, pipeline failures, and performance bottlenecks; perform root-cause analysis and implement durable, long-term solutions.</li>
<li>Continuously optimize data pipeline performance, reliability, and scalability to ensure fast, consistent, and dependable access to data.</li>
<li>Implement automated data quality checks, validation rules, and monitoring dashboards to ensure accuracy, consistency, and trust in delivered datasets.</li>
<li>Monitor, analyze, and manage data pipeline and compute costs across Azure, Databricks, and Microsoft Fabric, recommending and implementing cost-optimization strategies without compromising performance or availability.</li>
<li>Automate routine and repetitive data engineering tasks, applying best practices for CI/CD, deployment, testing, and operational support.</li>
<li>Design, implement, and maintain secure data access controls using role-based access, audits, and governance best practices to ensure appropriate data security and compliance.</li>
<li>Maintain clear, accurate, and up-to-date technical documentation, and provide ongoing operational support as data platforms and business needs evolve.</li>
<li>Stay current with emerging data engineering technologies, cloud services, and analytics best practices, and evaluate new tools through proofs of concept when appropriate.</li>
<li>Collaborate closely with product managers, software engineers, analysts, and operations teams to embed high-quality data solutions into core business processes.</li>
<li>Promote and enforce data engineering best practices including version control, modular and reusable pipeline design, documentation standards, and scalable architecture patterns.</li>
<li>Enable and support data democratization by providing well-modeled, secure, and self-service-ready datasets through Power BI, Microsoft Fabric, or custom analytics solutions.</li>
<li>Deliver measurable outcomes such as highly reliable pipelines with minimal manual intervention, on-time pipeline execution within service windows, rapid resolution of critical incidents, and consistently high data quality.</li>
<li>Ensure reusable and standardized pipeline components are leveraged across teams to accelerate delivery, improve consistency, and reduce operational overhead.</li>
<li>Provide stakeholders with reliable, well-modeled datasets that can be confidently explored without requiring ongoing engineering support.</li>
<li>Ensure all data solutions comply with organizational security, access, and governance policies while maintaining positive feedback from internal and external users.</li></ul> 


 Required Skills &amp; Qualifications 
<ul>
<li>3&ndash;5 years of hands-on experience in data engineering or related roles, with proven experience building, supporting, and operating production-grade data pipelines.</li>
<li>Strong hands-on experience with Databricks, including development, optimization, and operational support of Databricks-based data solutions.</li>
<li>Proven experience with Azure Data Factory (ADF) and Microsoft Fabric for data ingestion, orchestration, and transformation.</li>
<li>Advanced proficiency in SQL for querying, data modeling, performance tuning, and troubleshooting.</li>
<li>Strong programming skills in Python for data transformation, automation, scripting, and pipeline development.</li>
<li>Hands-on experience with Microsoft Azure cloud services related to data storage, compute, networking, and security.</li>
<li>Solid understanding of ETL/ELT patterns, data integration strategies, and real-time or near-real-time data processing concepts.</li>
<li>Experience designing metadata-driven and reusable pipeline components that scale across multiple teams and projects.</li>
<li>Strong understanding of data governance, data quality frameworks, monitoring practices, and automated validation techniques.</li>
<li>Experience supporting high-availability data platforms with SLAs, monitoring, alerting, and incident response processes.</li>
<li>Demonstrated ability to optimize cloud compute usage and manage costs efficiently across Azure, Databricks, and Microsoft Fabric.</li>
<li>Experience using version control systems such as Git and following modern software engineering best practices.</li>
<li>Ability to design secure, scalable, and cost-effective data architectures aligned with business needs.</li>
<li>Strong analytical, problem-solving, and troubleshooting skills with a proactive and ownership-driven mindset.</li>
<li>Excellent communication skills, with the ability to explain complex data concepts to both technical and non-technical stakeholders.</li>
<li>Ability to work independently as well as collaboratively in cross-functional team environments.</li>
<li>High attention to detail with a strong focus on data accuracy, reliability, and documentation quality.</li>
<li>Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field.</li>
<li>Relevant certifications are required or strongly preferred, including Databricks Certified Data Engineer, Microsoft Certified: Azure Data Engineer Associate, and Microsoft Certified: Fabric Data Engineer Associate.</li></ul> 


What We Offer
<ul>
<li>A team of bright, hard-working, and innovative people that will contribute to your growth.</li>
<li>Competitive Salary and comprehensive benefits plan.</li>
<li>A dynamic and collaborative work environment with opportunity to work with cutting-edge technology and innovative solutions.</li></ul> 


Other 
This is a full-time office based job in Islamabad, Pakistan. 
Closing

Mobiz embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. We are an equal opportunity employer.

We thank all applicants for their interest. We will contact you if you are selected to move forward in the recruiting process.</div>

Data Engineer

ImagineArt

<div><h3 class="jobSectionHeader">Who We Are</h3>
Vyro is redefining the future of digital creativity. We build cutting-edge content creation tools powered by Artificial Intelligence and Machine Learning, helping millions of creators, designers, and storytellers bring their imagination to life &mdash; effortlessly.
With a global user base of over 5 million active creators every month, Vyro&rsquo;s 20+ AI-powered apps are transforming how people design, edit, and express themselves across images, videos, and beyond.
From intuitive AI photo editors to next-gen video creation platforms, our products are designed to make creativity accessible, fast, and limitless.
At Vyro, we&rsquo;re a team of innovators, builders, and dreamers &mdash; known as Vyronauts &mdash; driven by passion, purpose, and the belief that technology should inspire creativity, not complicate it.
If you&rsquo;re excited about shaping the next wave of AI-powered creativity, Vyro is the place to be. 
 
Overview
We are seeking a highly experienced Senior Big Data Developer to design, build, and optimize large-scale data systems and backend infrastructure. The ideal candidate will have strong expertise in BigQuery, distributed data processing, and cloud-based data platforms, and will play a critical role in developing scalable data pipelines and backend services that support analytics, AI, and product systems.
This role requires deep technical expertise in handling large datasets, optimizing data workflows, and building reliable, production-grade data infrastructure.<h2 class="jobSectionHeader">
Responsibilities</h2><ul><li>
Design, build, and maintain scalable data pipelines and backend systems for processing large-scale datasets 
Develop, optimize, and manage complex queries, datasets, and workflows in BigQuery and data warehouse systems</li><li>
Build robust ETL/ELT pipelines to ingest, transform, and process data from multiple sources</li><li>
Develop backend services and data processing systems using languages such as Go, Python.</li><li>
Ensure high performance, scalability, reliability, and cost efficiency of data systems</li><li>
Integrate data systems with cloud services, APIs, and distributed systems</li><li>
Monitor, troubleshoot, and optimize data pipelines and backend infrastructure</li><li>
Collaborate with data scientists, analysts, and engineering teams to support analytics and AI-driven features</li><li>
Design clean, efficient, and maintainable system architecture</li><li>
Mentor junior engineers and contribute to technical leadership and architectural decisions</li></ul>
Requirements<ul><li>
5+ years of experience in Big Data, backend engineering, or data infrastructure roles</li><li>
Strong hands-on experience with BigQuery or similar data warehouse technologies (Snowflake, Redshift, Databricks, etc.)</li><li>
Strong proficiency in at least one programming language such as Go, Python, Node.js, or Java</li><li>
Strong expertise in SQL and query performance optimization</li><li>
Experience building and maintaining ETL/ELT pipelines</li><li>
Experience working with large-scale datasets and distributed systems</li><li>
Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure</li><li>
Strong understanding of data architecture, scalability, and performance optimization</li><li>
Excellent problem-solving and debugging skills</li></ul>
Preferred Qualifications<ul><li>
Experience with GCP services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Run</li><li>
Experience with Apache Spark, Kafka, or Airflow</li><li>
Experience supporting analytics, AI, or machine learning systems</li><li>
Experience with real-time and batch data processing systems</li><li>
Experience with microservices architecture</li></ul></div>

Senior Big Data Developer

Fusemachines

<div>
 
 About Fusemachines
 
 
 
 Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 
 
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 
 
 Type: Remote, Full-time
 
 
 Job Description:
 
 
 This is a role responsible for designing, building, and maintaining the automated testing frameworks and Python SDKs required for data integration, parity verification, and user accessibility in the Industrial IoT / Smart Buildings domain.
 
 
 We are seeking a Senior Data Engineer with strong Python and PySpark skills, and proven implementation of automated Data Quality frameworks and CI/CD pipelines, delivering Data and Analytics products using Agile methodology. The ideal candidate will possess strong technical, analytical, and interpersonal skills.
 
 
 Qualification / Skill Set Requirement:
 
 
 <ul>
 <li>
 5+ years of hands-on data engineering experience with deep expertise in the Azure ecosystem
 </li>
 <li>
 Expert Python skills (building Libraries/SDKs, Py4J)
 </li>
 <li>
 Strong experience with PySpark and DataFrames
 </li>
 <li>
 Experience with Automated Testing frameworks (PyTest, JUnit) for data pipelines
 </li>
 <li>
 Experience with Data Quality tools (Great Expectations, Deequ)
 </li>
 <li>
 Deep understanding of Apache Spark Internals (Catalyst Optimizer, Logical Plans)
 </li>
 <li>
 Experience with Databricks and Delta Lake optimization
 </li>
 <li>
 Solid understanding of SDLC and Agile methodologies with hands-on experience in Azure DevOps, GitHub, CI/CD, and artifact management
 </li>
 <li>
 Skilled in data modeling, data design, and data warehousing solutions on Azure Databricks
 </li>
 <li>
 Knowledge of data governance, and security best practices within Azure (AD, NSG, encryption, compliance)
 </li>
 <li>
 Certifications preferred: Azure Fundamentals, Azure Data Engineer Associate, Databricks Certified Data Engineer Professional and Azure Solutions Architect Expert (nice to have)
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Implement scalable and efficient data solutions on Spark and Flink
 </li>
 <li>
 Develop a Python SDK that wraps core libraries for use in Jupyter Notebooks by data scientist and analyst.
 </li>
 <li>
 Build automated Parity Test Suite: CI/CD pipeline that runs queries against "Golden Datasets" in both Spark and Flink and asserts equality
 </li>
 <li>
 Implement Data Quality (DQ) Rules configuration: Defining thresholds for "Completeness" and "Validity" that can be enforced
 </li>
 <li>
 Manage and optimize Azure and Databricks resources, for performance, reliability, and cost-efficiency
 </li>
 <li>
 Transform, clean, and prepare data using SQL, Python and Java
 </li>
 <li>
 Monitor and fine-tune workloads and pipelines for optimal performance and reliability
 </li>
 <li>
 Maintain CI/CD pipelines
 </li>
 <li>
 Maintain clear documentation of solutions, configurations, and workflows
 </li>
 <li>
 Actively participate in Agile team activities and continuous improvement initiatives
 </li>
 <li>
 Promote and enforce data engineering best practices, including data governance, security, and data quality
 
 
 </li>
 </ul>
 Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
 
 
 Powered by JazzHR
 
 
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</div>

Sr. Databricks Azure Data Engineer

Skylabs AI

<div>About Us
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
The Role
We are seeking an exceptional Senior AI Research Engineer with a strong focus on training and improving LLMs across the full lifecycle&mdash;from Domain‑Adaptive Pretraining to Supervised Fine‑Tuning (SFT), RL/RLVR, and advanced post‑training techniques (e.g., reward modeling, preference optimization, RL‑VR style workflows). You will lead hands‑on training efforts, contribute to research direction, and build robust pipelines for data, training, evaluation, and deployment.
You should have in‑depth understanding of LLM internals (attention/MLP dynamics, normalization, optimization behavior, scaling laws), and modern architectures including Mixture of Experts (MoE) and other frontier design choices. You will work closely with product and platform teams to translate research ideas into performant systems.
Requirements
Key Responsibilities<ul>
<li>
Lead the team of AI Engineers/Researchers
</li><li>Train and iterate on LLMs end-to-end across DAPT/CPT, SFT, and RL-based post-training (preference optimization, reward modeling, verifiable rewards, policy optimization, and related variants).
</li><li>Design training recipes: tokenization strategy, curriculum/sampling, batch/sequence packing, optimizer + scheduler choices, stability techniques, and hyperparameter search.
</li><li>Architect and implement efficient training systems using distributed training (data/tensor/pipeline parallelism), FSDP/ZeRO, activation checkpointing, mixed precision, and throughput optimization.
</li><li>Develop and maintain LLM data pipelines: large-scale data ingestion, filtering, deduplication, contamination checks, domain balancing, safety filtering, and dataset versioning.
</li><li>Perform deep EDA and root-cause analysis for training/eval regressions (loss spikes, instability, alignment drift, memorization, toxicity, domain overfitting), and implement mitigations.
</li><li>Build evaluation and benchmarking suites: offline metrics, human preference pipelines, automatic evals, domain-specific test sets, adversarial probing, and model behavior tracking over time.
</li><li>Apply and advance model compression and efficiency: distillation from LLMs, quantization-aware considerations, pruning/sparsity (including MoE routing behavior), and inference-time optimization tradeoffs.
</li><li>Implement and operationalize LLMOps: experiment tracking, reproducible runs, model registry, training telemetry, artifact management, CI for training configs, and safe rollout strategies.
</li><li>Leverage AI coding tools (e.g., Cursor, Copilot) to accelerate development while maintaining strong engineering rigor, testability, and code review standards.
</li><li>Collaborate cross-functionally with platform, infra, and product teams to integrate trained models into agentic/production pipelines (retrieval, tool use, evaluation gates, monitoring).
</li><li>Stay current with the field and translate new ideas (architectures, post-training, data strategies, evals) into internal experiments and improvements.
</li></ul>Qualifications &amp; Skills<ul>
<li>
5+ years in ML engineering / applied research, with significant hands-on experience training large models, especially LLMs.
</li><li>Strong practical knowledge of transformer internals and modern variations (MoE, routing, load balancing, attention variants, normalization choices, long-context strategies).
</li><li>Demonstrated experience with DAPT/CPT, SFT, and RL-based post-training (e.g., reward modeling, preference datasets, verifiable rewards, policy optimization). Ability to reason about why a method works and when it fails.
</li><li>Excellent understanding of data science fundamentals: EDA, dataset design, bias/contamination, sampling strategies, and error analysis.
</li><li>Proven ability to root-cause and debug training instabilities and performance regressions (numerics, data issues, infra bottlenecks, config drift).
</li><li>Expert-level programming in Python, with strong software engineering fundamentals (data structures, algorithms, systems thinking).
</li><li>Experience with key tooling such as PyTorch, distributed training frameworks (FSDP/DeepSpeed/ZeRO), and training orchestration.
</li><li>Familiarity with LLMOps: tracking (e.g., W&amp;B/MLflow), dataset versioning, reproducibility, deployment constraints, and monitoring of model behavior.
</li><li>Comfortable building agentic pipelines around LLMs (evaluation agents, data generation/labeling loops, model-in-the-loop distillation, automated red-teaming).
</li><li>Bonus: publications, open-source contributions, or demonstrated leadership in shipping LLM training improvements.
</li></ul>Who You Are
You&rsquo;re a pragmatic researcher-engineer: you can read papers, run experiments, and also build the training and data systems that make results reproducible and shippable. You&rsquo;re meticulous about data and measurement, fast at debugging, and comfortable making tradeoffs between quality, cost, and timeline. You communicate clearly, mentor others, and thrive in an environment where you&rsquo;re trusted to drive big initiatives.
Benefits<ul>
<li>
Salaries in USD (income tax exemptions)</li>
<li>Work in Pakistan Timezone</li>
<li>Comprehensive health allowance</li>
<li>Monthly team events and activities</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Opportunity to work with top minds in the industry and academia</li>
<li>Startup culture where ideas are heard at all levels</li>
<li>Adequate annual, sick, casual and parental leaves</li></ul></div>

Senior AI Research Engineer

Career Development Center COMSATS University Islamabad-Islamabad Campus

<div>
 Tajir is a fast-growing B2B commerce startup transforming Pakistan&rsquo;s retail industry through technology. We build scalable software systems that power thousands of retailers, enabling them to procure inventory seamlessly and operate more efficiently.
 
 
 Tajir is backed by leading global investors including Kleiner Perkins and Y Combinator, and we are focused on building a strong engineering and data team to solve real-world problems at scale.
 
 
 
 We Are Currently Hiring
 
 
 
 Software Engineer (Fresh Graduates &amp; Experienced)
 
 
 Software Engineer Intern (3rd Year Students)
 
 
 Data Scientist (Fresh Graduates &amp; Experienced)
 
 
 Data Scientist Intern (3rd Year Students)
 
 
 Apply at
 
 https://jobs.ashbyhq.com/tajir
 
 
 .
 
</div>

Tajir | Software & Data Roles

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