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machine learning engineer

NESL-IT (SMC PVT) LTD

Location: Onsite &mdash; Islamabad (I-10/3) Employment Type: Full-time (6 pm to 2 am) We are seeking a skilled and highly motivated AI/ML Engineer with 4+ years of hands-on experience in designing, developing, deploying, and optimizing machine learning models and AI-driven solutions. The ideal candidate will have a strong background in ML algorithms, deep learning frameworks, data engineering, and model deployment in production environments.Key Responsibilities<ul><li>Design, develop, and deploy machine learning and deep learning models for real-world applications.</li><li>Build scalable data pipelines, preprocess datasets, and perform feature engineering.</li><li>Develop, fine-tune, and evaluate models using frameworks such as TensorFlow, PyTorch, Scikit-learn.</li><li>Work closely with data engineers, software engineers, and product teams to translate business needs into ML solutions.</li><li>Deploy and monitor models using MLOps tools (Docker, Kubernetes, MLflow, AWS/GCP/Azure services).</li><li>Conduct research on new algorithms, technologies, and tools to enhance model accuracy and performance.</li><li>Build REST APIs or microservices to integrate models into production systems.</li><li>Analyze model performance, optimize pipelines, and troubleshoot issues in production.</li><li>Create thorough technical documentation and communicate findings effectively.</li></ul>Required Skills &amp; Qualifications<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Data Science, Software Engineering, or related field.</li><li>4+ years of experience in Machine Learning, Artificial Intelligence, or Data Science.</li><li>Strong understanding of ML concepts: supervised/unsupervised learning, NLP, computer vision, time-series, etc.</li><li>Hands-on experience with Python, including NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.</li><li>Experience with MLOps, CI/CD pipelines, and cloud platforms (AWS/GCP/Azure).</li><li>Solid understanding of data preprocessing, model evaluation, tuning, and validation techniques.</li><li>Strong problem-solving skills and the ability to work independently in a fast-paced environment.</li><li>Experience with large language models (LLMs) and prompt engineering is a plus.</li><li>Knowledge of big data tools (Spark, Hadoop) is a plus.</li></ul>Job Type: Full-timePay: Rs150,000.00 - Rs200,000.00 per monthExperience:<ul><li>B2B Sales: 5 years (Required)</li></ul>Work Location: In person

AI/ML Engineer

Cloudelligent

<div>Position Title: Sr. AWS AI Engineer 
Location: Islamabad 
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> 

Eddu0LEAtX</div>

Sr. AWS AI Engineer

Creativelogicx

<ul><li>Design machine learning systems</li><li>Research and implement machine learning algorithms and tools</li><li>Manage and direct research and development processes to meet the needs of our AI strategy</li><li>Develop machine learning applications in alignment with project requirements and business goals</li><li>Perform machine learning tests and statistical analysis in order to fine-tune the machine learning systems</li><li>Select appropriate datasets and data representation methods</li><li>2+ years of experience applying AI to practical uses</li><li>Experience with deep learning, NLP, and TensorFlow</li><li>Experience writing robust code in Python, Java, and/or R</li><li>Experience in REST API development, NoSQL database design, and RDBMS design and optimizations</li><li>Knowledge of basic algorithms and object-oriented and functional design principles</li><li>Knowledge of data structures, data modeling, and software architecture</li></ul>Job Type: Full-timeWork Location: In person

ZZ-Technologies, islamabad

Job Summary:We are seeking a skilled and innovative AI Engineer to design, develop, and implement AI-driven solutions to support our products and operations. The ideal candidate will have strong experience in machine learning, deep learning, data processing, and software engineering.Responsibilities:LLM Development &amp; Fine-Tuning<ul><li>Fine-tune and adapt state-of-the-art LLMs (e.g., LLaMA, GPT, Mistral, Gemma) for domain-specific tasks.</li><li>Implement advanced training strategies including LoRA, QLoRA, PEFT, and parameter-efficient adaptation methods.</li><li>Manage dataset preprocessing, curation, augmentation, and experiment tracking.</li><li>Optimize models for quality, latency, and memory efficiency across training and inference.</li></ul>GPU-Based Training &amp; Optimization<ul><li>Run and optimize training pipelines across multi-GPU environments (NVIDIA A100, H100, RTX, etc.).</li><li>Implement mixed-precision training, quantization, and distributed training (e.g., DeepSpeed, FSDP, DDP).</li><li>Monitor GPU performance, memory usage, and throughput to ensure optimal resource utilization.</li></ul>Model Serving &amp; Infrastructure<ul><li>Deploy LLMs using modern serving frameworks (vLLM, TensorRT-LLM, HuggingFace TGI, Triton).</li><li>Develop scalable inference architectures using Docker, Kubernetes, and cloud GPU infrastructure.</li><li>Build end-to-end pipelines for continuous training, evaluation, and automated deployment.</li></ul>Research, Experimentation &amp; Innovation<ul><li>Stay updated with cutting-edge research in transformers, embeddings, RAG, PEFT, and efficient fine-tuning.</li><li>Run experiments, benchmark models, and propose architectural or training improvements.</li><li>Prototype new capabilities and develop internal best practices for LLM workflows.</li></ul>Collaboration &amp; Leadership<ul><li>Work closely with product, engineering, and data teams to translate requirements into model behaviors.</li><li>Mentor junior engineers and contribute to technical design reviews and architecture decisions.</li><li>Communicate model performance, limitations, and trade-offs clearly to stakeholders</li></ul>Requirements:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Data Science, Engineering, or a related field.</li><li>Strong coding skills in Python (TensorFlow, PyTorch, Scikit-learn, OpenCV, etc.).</li><li>Solid understanding of machine learning algorithms, deep learning, NLP, or computer vision.</li><li>Experience with cloud platforms (AWS, Azure, GCP) is a plus.</li><li>Familiarity with MLOps tools (Docker, Kubernetes, MLflow, etc.) preferred.</li><li>Strong problem-solving skills and ability to work on complex, data-driven problems.</li><li>Ability to work collaboratively in a team-oriented environment.</li></ul>Preferred Qualifications:<ul><li>Experience deploying AI models in production environments.</li><li>Knowledge of LLMs (Large Language Models) and prompt engineering.</li><li>Background in data engineering or backend development.</li><li>Research experience or publications in AI/ML fields.</li></ul>You can share your cv on whtsapp as well. 03355707047Job Type: Full-timePay: Rs200,000.00 - Rs500,000.00 per monthWork Location: In person

Senior AI Engineer

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>

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>
olqQlu28No</div>

Information Tech Consultants

<div>
 
 🌟 Senior Data Scientist SME /
 
 Data Science SME (Subject matter expert)
 
 🧠
 
 
 
 
 
 
 Location : London (Relocation required - Sponsorship will be provided)
 
 
 
 
 Experience : 9-12 years
 
 
 
 
 CTC- 40-45 lacs
 
 
 
 
 
 
 We are seeking a highly accomplished and results-oriented
 
 Senior Data Scientist Subject Matter Expert (SME)
 
 with over
 
 10 years of experience
 
 to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including
 
 Generative AI, Computer Vision, and Natural Language Processing (NLP)
 
 .
 
 
 You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes.
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 
 AI/ML Strategy &amp; Architecture:
 
 Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving
 
 Generative AI (GenAI)
 
 , large language models (
 
 LLMs
 
 ), and specialized models in Computer Vision and NLP.
 </li>
 <li>
 
 Big Data Engineering:
 
 Design, build, and optimize high-throughput, distributed data pipelines and features using
 
 Apache Spark (Scala)
 
 and
 
 Hive
 
 on massive datasets to support model training and inference.
 </li>
 <li>
 
 Cross-Cloud Execution:
 
 Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (
 
 AWS, Azure, and GCP
 
 ), ensuring portability, scalability, and cost efficiency.
 </li>
 <li>
 
 Specialized Model Development:
 
 Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas:
 </li>
 <li>
 
 Computer Vision:
 
 Developing and optimizing models for image recognition, object detection, and video analytics.
 </li>
 <li>
 
 NLP:
 
 Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs.
 </li>
 <li>
 
 Generative AI:
 
 Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features.
 </li>
 <li>
 
 SME Consulting &amp; Mentorship:
 
 Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams.
 </li>
 <li>
 
 MLOps &amp; Governance:
 
 Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment.
 </li>
 </ul>
 
 
 
 
 Required Skills and Expertise (10+ Years)
 
 
 
 
 
 
 
 
 1. Big Data and Cloud Mastery
 
 
 
 
 <ul>
 <li>
 
 Programming &amp; Big Data:
 
 10+ years of extensive, hands-on experience with
 
 Apache Spark
 
 , with strong preference for production development using
 
 Scala
 
 . Deep expertise with
 
 Apache Hive
 
 for data querying and management.
 </li>
 <li>
 
 Cloud Proficiency:
 
 Demonstrated expertise in deploying and managing data/ML workloads across
 
 at least two
 
 of the three major cloud platforms:
 
 AWS
 
 (Sagemaker, EMR, S3),
 
 Azure
 
 (Azure ML, Synapse Analytics), and
 
 GCP
 
 (Vertex AI, BigQuery).
 </li>
 <li>
 
 Data Architecture:
 
 Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context.
 </li>
 </ul>
 
 
 
 
 2. Advanced AI/ML Specialization
 
 
 
 
 <ul>
 <li>
 
 Generative AI (GenAI) &amp; LLMs:
 
 Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying
 
 Large Language Models (LLMs)
 
 .
 </li>
 <li>
 
 Computer Vision:
 
 In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO).
 </li>
 <li>
 
 NLP:
 
 Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications.
 </li>
 </ul>
 
 
 
 
 3. Leadership &amp; Soft Skills
 
 
 
 
 <ul>
 <li>
 
 Technical Leadership:
 
 Proven track record of leading complex data science projects from research to production deployment.
 </li>
 <li>
 
 Communication:
 
 Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences.
 </li>
 <li>
 
 Mentorship:
 
 Experience mentoring and training senior engineers and data scientists.
 </li>
 </ul>
 
 
 
 
 Education and Certification
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field.
 </li>
 <li>
 Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.
 </li>
 </ul>
 
 
</div>

Senior Data Scientist SME & AI

Explore 269+ Machine learning engineer in Islamabad Pakistan this January. Find roles across top companies and apply now to boost your career.

269 machine learning engineer jobs IN Islamabad Pakistan

AI/ML Engineer

Sr. AWS AI Engineer

AI/ML Engineer

Senior AI Engineer

AI Data Scientist

AI Data Scientist

Senior Data Scientist SME & AI