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eSpark Talent

AI/ML Research Intern &ndash; Quant &amp; Financial IntelligenceeSpark Talent is seeking exceptionally talented and highly driven individuals focused on quantitative finance, market prediction, and advanced machine learning. This role is designed for builders, problem-solvers, and researchers who want real-world exposure to financial AI systems and quantitative modelling. We want individuals who can think creatively, experiment rigorously, and build high-impact models.Key Responsibilities:<ul><li>Develop predictive ML models for equities, options, and market microstructure.</li><li>Engineer novel features such as volatility indicators, gamma exposure signals, and flow-based metrics.</li><li>Build and optimize ensemble architectures across classifiers, regressors, and time-series models.</li><li>Design backtesting and simulation frameworks for evaluating predictive signals.</li><li>Work with large-scale, noisy, real-time financial datasets.</li><li>Automate pipelines for data ingestion, cleaning, normalization, and labeling.</li><li>Experiment with feature extraction, including deep-learning-based embeddings.</li><li>Analyze model performance across various market regimes and conditions.</li><li>Present weekly research updates, insights, and model enhancements.</li><li>Prepare explainability reports (SHAP, ICE plots, feature attributions).</li></ul>Requirements:<ul><li>Demonstrated expertise through Kaggle competitions, notebooks, or structured ML pipelines.</li><li>Strong capability in cleaning, engineering, and synthesizing large, complex, and noisy datasets.</li><li>Experience with model stacking/ensembles, feature engineering, experimental design, and optimizing ML workflows.</li><li>Strong knowledge of Market prediction tasks like classification, regression, forecasting, volatility modelling.</li><li>Concepts such as Options Greeks, GEX, volatility surfaces, order flow, and market microstructure (highly preferred).</li><li>Evaluation methodologies using financial metrics (Sharpe ratio, drawdown, expectancy).</li><li>Handling non-stationary data, regime shifts, and applying walk-forward testing.</li><li>Proficiency in Python (NumPy, Pandas, Scikit-Learn, PyTorch/TF/JAX).</li><li>Experience with experiment tracking tools (MLflow, Weights &amp; Biases).</li><li>Ability to write clean, modular, research-grade code.</li><li>Capability to implement research papers and reproduce results from scratch.</li></ul>Qualifications: Bachelor&rsquo;s degree in CS, Data Science, Mathematics, Engineering, or a related field.Preferred Skills:<ul><li>Experience with deep learning for tabular or time-series models.</li><li>Knowledge of derivatives concepts (gamma, vanna, skew, etc.).</li><li>Prior exposure to quantitative research projects, university competitions, or academic papers.</li></ul>Benefits:<ul><li>Paid 3-month internship with hands-on quantitative research.</li><li>Direct mentorship from senior AI, ML, and quant research leaders.</li><li>Access to real, institutional-grade financial datasets.</li><li>Weekly research sprints and iterative project cycles.</li><li>State-of-the-art tooling, cloud access, and GPU compute resources.</li><li>Opportunity for a full-time role upon successful performance</li></ul>Job Type: Full-timeWork Location: In person

AI/ML Intern

NorthBay Solutions

<div><h3 class="jobSectionHeader">Lead GenAI Engineer (Application Development)</h3>
Experience: 7&ndash;12+ years 
Location: Hybrid (Lahore / Karachi / Islamabad &ndash; Pakistan) 
Employment Type: Full-time<h4 class="jobSectionHeader">
About the Role</h4>
NorthBay Solutions is seeking a Lead GenAI Engineer (Application Development) with a strong foundation in AI/ML, GenAI solution design, and end-to-end application development. The ideal candidate will have a proven track record of developing and deploying enterprise-scale GenAI applications across cloud and hybrid environments, while leading cross-functional engineering teams in Agile settings.<h4 class="jobSectionHeader">
Core Responsibilities</h4><ul><li>
Design and implement AI-powered enterprise-grade applications, integrating traditional systems with AI/ML and GenAI capabilities.</li><li>
Lead a team of 8&ndash;12 engineers across full-stack, DevOps, and AI/ML disciplines.</li><li>
Drive technical decision-making across infrastructure, microservices, APIs, and AI components.</li><li>
Architect and deliver production-ready GenAI applications, ensuring scalability, reliability, and performance.</li><li>
Collaborate with product and business teams to translate complex requirements into actionable AI-driven solutions.</li></ul><h4 class="jobSectionHeader">
Technical Requirements</h4>
GenAI Leadership (3+ Years) &ndash; Primary<ul><li>
Proven experience in developing and deploying GenAI applications in production.</li><li>
Expertise in LLMs (LLAMA, Mistral, GPT, etc.), including fine-tuning, optimization, and deployment.</li><li>
Hands-on experience with Agentic AI, Multi-Agent Systems, and Agentic RAG implementations.</li><li>
Proficiency in Vector Databases, LangChain, LangGraph, and related toolchains.</li><li>
Strong prompt engineering and Chain-of-Thought optimization capabilities.</li></ul>
AI/ML Foundation (4&ndash;5 Years)<ul><li>
Hands-on Python, TensorFlow, PyTorch experience for building ML models and AI pipelines.</li><li>
Expertise in the AI/ML model lifecycle &mdash; from development and deployment to monitoring.</li><li>
Experience integrating AI/ML solutions into enterprise-grade web or mobile applications.</li></ul>
Application Development &amp; Architecture (7+ Years)<ul><li>
Strong background in full-stack development (MERN or equivalent stack).</li><li>
Proven ability to deliver end-to-end applications integrating AI/ML and GenAI capabilities.</li><li>
Proficiency in API development (REST, GraphQL) and microservices architecture.</li><li>
Experience deploying solutions across on-premises, cloud, and hybrid environments.</li><li>
Kubernetes for container orchestration and deployment management.</li><li>
Database experience in SQL (PostgreSQL/MySQL) and NoSQL (MongoDB/DynamoDB).</li><li>
Familiarity with DevOps tools: Docker, CI/CD pipelines, and infrastructure automation.</li></ul>
Cloud &amp; Infrastructure<ul><li>
Hands-on experience with AWS/Azure/GCP cloud environments and ML services.</li><li>
Experience with AWS SageMaker, Bedrock, Lambda, API Gateway, or equivalents.</li><li>
Understanding of hybrid architecture design integrating AI/ML systems.</li></ul><h4 class="jobSectionHeader">
Proven Delivery</h4><ul><li>
Successful delivery of 7+ enterprise or AI/ML-driven applications.</li><li>
Demonstrated leadership experience managing cross-functional technical teams.</li><li>
Ability to deliver high-quality, scalable, and secure solutions under tight timelines.</li></ul><h4 class="jobSectionHeader">
Preferred Qualifications</h4><ul><li>
Cloud certifications (AWS/Azure/GCP &ndash; Solutions Architect / ML Specialty preferred).</li><li>
Excellent communication and leadership skills, capable of bridging business and technology.</li><li>
Experience working in Agile/Scrum environments with measurable performance outcomes.</li></ul><h4 class="jobSectionHeader">
Ideal Candidate</h4>
A hands-on leader with strong expertise in GenAI application development, solid understanding of AI/ML, and a proven background in enterprise software engineering and deployment across cloud and hybrid infrastructures.
TKy0yLI6H2</div>

Lead GenAI Engineer (Application Development)

VentureDive

<div>Job Brief 
We are seeking a highly skilled Data &amp; AI Architect to design and implement scalable, secure, and high-performance data and AI architectures across cloud and hybrid environments. The ideal candidate will have deep expertise in data engineering, machine learning, and AI solution design, with experience leveraging cloud-native and open-source technologies to deliver intelligent, data-driven solutions. This role demands strong technical leadership, architectural vision, and the ability to translate complex business requirements into cohesive Data &amp; AI ecosystems that support analytics, automation, and innovation. 
 
VentureDive Overview 
Founded in 2012 by veteran technology entrepreneurs from MIT and Stanford, VentureDive is the fastest-growing technology company in the region that develops and invests in products and solutions that simplify and improve the lives of people worldwide. We aspire to create a technology organization and an entrepreneurial ecosystem in the region that is recognized as second to none in the world. 
 
Key Responsibilities:<ul><li>
Architect, design, and implement end-to-end Data &amp; AI solutions across cloud, on-premises, or hybrid environments.</li><li>
Build Data ingestion, transformation, and storage pipelines for structured, semi-structured, and unstructured data sources.</li><li>
Design and implement AI/ML pipelines, including feature Agentic applications engineering, model training, deployment, and monitoring.</li><li>
Leverage modern Data and AI platforms (e.g., Databricks, Snowflake, BigQuery, Redshift, Synapse, Vertex AI, SageMaker, or Azure ML) to enable advanced analytics and predictive modeling.</li><li>
Collaborate with stakeholders to define Data and AI strategy, architecture blueprints, and technology roadmaps.</li><li>
Integrate ML models and AI services (e.g., generative AI, NLP, computer vision) into business workflows and enterprise applications.</li><li>
Implement data governance, model governance, and Responsible AI frameworks to ensure compliance, transparency, and ethical AI usage.</li><li>
Optimize pipelines and workflows for performance, scalability, and cost-efficiency.</li><li>
Partner with engineering and DevOps teams to establish MLOps and DataOps practices for continuous integration and deployment of models.</li><li>
Produce high-quality architecture documentation, data flow diagrams, and solution blueprints.</li><li>
Mentor engineers and data scientists, promoting best practices in data engineering, AI architecture, and cloud-native design.</li><li>
Stay current with emerging AI, LLM, and data technologies to evaluate their potential in enterprise and government use cases.</li></ul> 

Required Experience &amp; Qualification:<ul><li>
10+ years of experience in data engineering, data architecture, or AI solution design.</li><li>
Strong hands-on experience with data platform technologies, such as:</li><li>
Data pipelines: Apache Spark, Airflow, dbt, Kafka, Flink, or similar.</li><li>
Data storage: Data lakes, warehouses, and lakehouses (e.g., Snowflake, Delta Lake, BigQuery, Redshift, Synapse).</li><li>
AI/ML platforms: TensorFlow, PyTorch, scikit-learn, MLflow, or cloud ML platforms (Azure ML, SageMaker, Vertex AI).</li><li>
Proven experience building and deploying machine learning models at scale (batch, streaming, or real-time).</li><li>
Deep understanding of data lakehouse and data mesh architectures.</li><li>
Experience implementing governance, lineage, and security frameworks for data and AI systems.</li><li>
Strong communication and stakeholder management skills, with the ability to explain architectural concepts to diverse audiences.</li><li>
Demonstrated ability to balance innovation, scalability, and cost optimization in complex ecosystems.</li></ul> 

Preferred Skills:<ul><li>
Knowledge of Generative AI, LLMs, vector databases, and embedding-based retrieval (e.g., RAG architectures).</li><li>
Experience with MLOps tools (MLflow, Kubeflow, Vertex Pipelines, or Azure ML pipelines).</li><li>
Familiarity with DataOps and CI/CD practices for data and AI workflows.</li><li>
Integration of AI insights into BI or visualization tools (e.g., Power BI, Tableau, Looker).</li><li>
Exposure to real-time AI applications, including anomaly detection, predictive maintenance, or conversational AI.</li><li>
Experience leading data and AI modernization initiatives or enterprise AI strategy projects.</li><li>
Understanding of governance and compliance frameworks (GDPR, ISO 27001, NIST, or sector-specific standards).</li></ul> 
What we look for beyond required skills 
In order to thrive at VentureDive, you 
&hellip;are intellectually smart and curious 
&hellip;have the passion for and take pride in your work 
&hellip;deeply believe in VentureDive&rsquo;s mission, vision, and values 
&hellip;have a no-frills attitude 
&hellip;are a collaborative team player 
&hellip;are ethical and honest 
 
Are you ready to put your ideas into products and solutions that will be used by millions? 
You will find VentureDive to be a quick pace, high standards, fun and a rewarding place to work at. Not only will your work reach millions of users world-wide, you will also be rewarded with competitive salaries and benefits. If you think you have what it takes to be a VenDian, come join us ... we're having a ball! 
 
#LI-Hybrid
lSXDsfMqSd</div>

Data & AI Architect

Systems Limited

<div>
 
 We are looking for a seasoned AI/AIOps Engineer with deep expertise in building intelligent operational systems powered by modern LLMs, data engineering, and automation frameworks. The ideal candidate will lead the design and deployment of AI-driven solutions for event correlation, anomaly detection, incident prediction, and operational insights. This role requires strong technical leadership, hands-on development capability, and a proven track record of delivering measurable improvements in IT operations.
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Design, develop, and deploy AI/ML solutions for event correlation, log analysis, root cause prediction, and observability enhancement.
 </li>
 <li>
 Build and optimize LLM-powered systems, including RAG pipelines, MoE models, and vector-search architectures.
 </li>
 <li>
 Implement multi-model orchestration layers or MCP frameworks to manage diverse AI components and workflows.
 </li>
 <li>
 Collaborate with engineering, DevOps, and SRE teams to integrate AIOps capabilities into operational environments.
 </li>
 <li>
 Develop scalable APIs and backend services using Python and FastAPI.
 </li>
 <li>
 Leverage statistics, ML algorithms, and analytical techniques to generate actionable operational insights.
 </li>
 <li>
 Work with MLOps and AIOps toolchains to automate model deployment, monitoring, and maintenance.
 </li>
 <li>
 Evaluate system performance, drive continuous improvement initiatives, and deliver quantifiable operational benefits.
 </li>
 <li>
 Prepare documentation, architecture diagrams, and best practices for AI implementations.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, or a related technical field.
 </li>
 <li>
 5+ years of experience in AI/ML, Data Engineering, or AIOps domains.
 </li>
 <li>
 Demonstrated success implementing LLM-based solutions for log/event correlation, incident prediction, or operational intelligence.
 </li>
 <li>
 Strong understanding of AIOps concepts including event correlation, anomaly detection, incident prediction, and topology mapping.
 </li>
 <li>
 Hands-on experience with RAG workflows, MoE models, and vector databases (FAISS, Pinecone, Milvus).
 </li>
 <li>
 Proficient in Python, FastAPI, and AI integration frameworks such as LangChain, LlamaIndex, or Transformers.
 </li>
 <li>
 Experience building MCP or multi-model orchestration layers.
 </li>
 <li>
 Solid grounding in data science, statistics, and core ML algorithms.
 </li>
 <li>
 Familiarity with AIOps platforms like Moogsoft, BigPanda, Dynatrace, or IBM Watson AIOps.
 </li>
 <li>
 Proven impact with measurable outcomes (e.g., reduced alert noise, faster incident resolution).
 </li>
 </ul>
 
 
</div>

AI/ML Engineer

HR Ways

About the job Senior AI/ML Engineer - Remote from LahoreHiring Senior AI/ML Engineer - Remote from Lahore&#65279;Client Company Introduction:&#65279;An AI-based agriculture technology firm headquartered in Canada. &#65279; &#65279;Job Description:<ul><li>Data Preparation &amp; Baseline Model:</li></ul>Audit and validate annotated datasets for quality and consistency. Define data schema, coordinate systems, and identifiers. Implement preprocessing workflows (tiling, normalization, augmentation). Split data into training, validation, and test sets for robust evaluation. Train baseline object detection or counting models (e.g., YOLO, Faster R-CNN). Deliver baseline performance report with metrics (precision, recall, counting error).<ul><li>Model Optimization &amp; Calibration:</li></ul>Optimize model performance using hyper-parameter tuning and hard example mining. Validate across diverse conditions and unseen data. Implement geospatial alignment and calculate object densities or spatial statistics. Calibrate detection thresholds for precision and recall balance. Compare automated results with manual benchmarks and refine accordingly.<ul><li>Cloud Deployment &amp; Output Generation:</li></ul>Containerize models (Docker) and deploy on AWS or Azure using services like Sage Maker, ECS, or Azure ML. Automate inference pipelines integrated with S3, Blob Storage, or Data Lakes. Generate structured outputs (CSV, GeoTIFF, GeoJSON) for analytics and visualization. Expose APIs for inference job submission and results retrieval. Test scalability and runtime efficiency across sample datasets.<ul><li>Reporting, QA, and Knowledge Transfer:</li></ul>Develop automated reporting tools summarizing predictions and insights (PDF or dashboard format). Conduct end-to-end QA for accuracy, reliability, and coordinate integrity. Document workflows, performance benchmarks, and retraining processes. Provide knowledge transfer and technical training for internal teams.Required Skills &amp; Experience:<ul><li>5+ years of experience in Machine Learning, AI, or Computer Vision.</li><li>Expertise in Python, PyTorch/TensorFlow, OpenCV, and NumPy/Pandas.</li><li>Proficiency with annotation tools such as Roboflow and CVAT for dataset labeling and management.</li><li>Experience with cloud-based ML deployment on AWS or Azure.</li><li>Strong background in object detection, segmentation, and model optimization.</li><li>Familiarity with geospatial data processing (GDAL, GeoPandas, rasterio, shapely).</li><li>Proficiency with Docker, API development (FastAPI/Flask), and automation scripts.</li><li>Excellent documentation, reporting, and presentation skills.</li></ul>Other Details:<ul><li>Work Mode: Remote from Lahore</li><li>Experience: 5+ Years in AI/ML</li></ul><ul><li>Working Timings: 9am-6pm</li></ul>About HR Ways:HR Ways is an Award winning Technical Recruitment Firm helping software houses and IT Product companies internationally and locally to find IT Talent. HR Ways is engaged by 300+ Employers worldwide ranging from worlds biggest SaaS Companies to most competitive Startups. We have entities in Dubai, Canada, US, UK, Pakistan, India, Saudi Arabia, Portugal, Brazil and other parts of the world. &#65279;Join our WhatsApp Channel https://shorturl.at/983az to stay updated or visit www.hrways.co to know more.&quot;Job Type: Full-timeWork Location: In person

Senior AI/ML Engineer

Prime Care Medical Group PC

Senior Full-Stack Developer / Technical Lead &ndash; Healthcare, AR/VR, RetailLocation: Remote &ndash; Pakistan Employment Type: Full-time | 40 hours/week | 2-year contract Compensation: Negotiable (PKR) + milestone bonuses + advisory equity (vesting at contract completion) Reporting To: Country Lead &ndash; Pakistan Work Hours: 9:00 AM &ndash; 5:00 PM ESTAbout the RolePrime Care Medical Group PC is expanding its technology division in Pakistan. We are looking for a Senior Full-Stack Developer / Technical Lead to drive end-to-end development of healthcare and retail platforms. The role covers architecture, technical leadership, and delivery across full-stack solutions, including AI/ML, AR/VR, vector imaging, and embedded EMR modules.Key Responsibilities<ul><li>Architect and deliver full-stack solutions (backend APIs, cloud infrastructure, frontend UI/UX).</li><li>Integrate AI/ML, AR/VR, imaging, and EMR/CRM modules.</li><li>Ensure adherence to coding standards, documentation, and security/compliance (HIPAA/GDPR).</li><li>Mentor and coordinate support staff (QA, UI, DevOps).</li><li>Drive on-time releases and maintain high technical standards.</li></ul>Required Qualifications<ul><li>6+ years full-stack development experience, with at least 2 years in senior/lead roles.</li><li>Proficient in Node.js / Python / React / Next.js / SQL / NoSQL / REST / GraphQL.</li><li>Proven track record in delivering end-to-end software solutions.</li></ul>Preferred Skills<ul><li>Experience in healthcare, retail, AR/VR, or AI/ML platforms.</li><li>Knowledge of HIPAA/GDPR and medical data standards.</li><li>Experience mentoring or leading development teams.</li></ul>Benefits &amp; Incentives<ul><li>Negotiable monthly salary (PKR)</li><li>Milestone-based performance bonuses</li><li>Advisory equity (vesting after contract completion)</li><li>Fully remote role</li><li>Recognition and portfolio visibility across projects</li></ul>How to ApplySubmit your CV, portfolio, and a brief summary of projects you have led in healthcare, retail, or AR/VR systems. Only applicants based in Pakistan will be considered.Job Types: Full-time, Contract Contract length: 24 monthsWork Location: Remote

Senior Full-Stack Developer / Technical Lead (Healthcare / AR-VR / Retail Platform – Karachi)

Horizon Tech

We are looking for a skilled Data Engineer to design, build, and optimise our modern data platform on the cloud. You'll be responsible for architecting scalable, secure, and automated data pipelines and enabling data-driven applications and AI/ML solutions across the organisation.This is an exciting opportunity to shape the data foundation of a growing business, leveraging a modern AWS and engineering ecosystem.Must Haves:<ul><li>3-5 years of experience in data engineering or a similar role working with large-scale, distributed data systems.</li><li>Strong proficiency in Python, SQL, and data modelling for analytical and transactional systems.</li><li>Deep understanding of modern AWS data and analytics services (e.g., S3, Glue, Lambda, Redshift, or equivalents).</li><li>Experience with Apache Spark / PySpark for batch and stream processing.</li><li>Solid knowledge of data governance, security, and compliance frameworks.</li><li>Familiarity with Infrastructure as Code (Terraform, CloudFormation) and CI/CD practices.</li><li>Understanding of AI/ML data workflows, including feature engineering and data preparation for LLMs or predictive models.</li><li>Strong problem-solving, collaboration, and communication skills.</li></ul>Preferred (Nice to Have)<ul><li>Knowledge of containerization (Docker, ECS, EKS) or serverless data architectures.</li><li>Understanding of AI/ML and NLP technologies, including integration of LLMs, automation frameworks, and RPA tools for intelligent data workflows.</li><li>Awareness of MLOps pipelines, model monitoring, and feature store management.</li></ul>Responsibilities:<ul><li>Design, build, and maintain large-scale, distributed, and event-driven data pipelines using modern AWS Data Engineering services (e.g., Glue, Lambda, Step Functions, etc.).</li><li>Develop ETL/ELT workflows integrating structured and unstructured data into Snowflake, Redshift, and S3-based data lakes.</li><li>Architect and optimise data ingestion, transformation, and storage layers for structured and unstructured data in a data lake or warehouse environment.</li><li>Implement and enforce data security, governance, and access controlincluding encryption, IAM, auditing, and compliance with best practices.</li><li>Develop and maintain metadata management, data lineage, and cataloguing frameworks to ensure traceability and consistency across datasets.</li><li>Automate infrastructure provisioning using Infrastructure-as-Code (IaC) tools such as Terraform or AWS CloudFormation.</li><li>Collaborate with analytics and AI/ML teams to deliver clean, high-quality, and feature-ready data for training and inference pipelines.</li><li>Integrate observability and monitoring into data workflows to ensure reliability, performance, and cost efficiency.</li><li>Contribute to CI/CD pipelines and Git-based version control for data workflows and infrastructure changes.</li><li>Mentor junior engineers and champion engineering best practices for data quality, reliability, and scalability.</li></ul>Other Details<ul><li>Work Days: Monday-Friday (3 pm - 12 am)</li><li>Office location: Off to Shahrah-e-Faisal, PECHS, Karachi</li></ul>Job Type: Full-timePay: Rs150,000.00 - Rs250,000.00 per monthApplication Question(s):<ul><li>What is your expected salary?</li></ul>Education:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>data engineering with large-scale data systems: 3 years (Required)</li><li>Python, SQL and modern AWS data and analytics services: 3 years (Required)</li><li>ETL/ELT workflows : 3 years (Required)</li></ul>Location:<ul><li>Karachi (Required)</li></ul>Work Location: In person

Data Engineer

Explore 287+ Ai ml intern in Karachi Pakistan this November. Find roles across top companies and apply now to boost your career.