machine learning engineer

Tamara

<div><p><b>About Us</b></p>
<p>
Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.</p>
<p>
Tamara is Saudi Arabia&rsquo;s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.</p>
<p><b>
Your Role</b></p>
<p>
We are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.</p>
<p>
You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.</p>
<p><b>
Your Responsibilities</b></p>
<p><b>
Model Deployment &amp; Scaling</b></p><br>
<ul>
<li>Productionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architectures</li>
<li>Design low-latency, high-availability APIs and pipelines for real-time model inference.</li>
<li>Implement batch scoring systems for periodic risk assessments.=</li>
</ul>
<p><b>MLOps &amp; Infrastructure</b></p>
<ul>
<li>Build and maintain CI/CD pipelines for model deployment and monitoring.</li>
<li>Set up automated feature engineering pipelines, leveraging feature stores.</li>
<li>Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.</li>
</ul>
<p><b>Model Monitoring &amp; Maintenance</b></p>
<ul>
<li>Implement real-time and batch monitoring for data drift, concept drift, and model performance.</li>
<li>Build automated retraining workflows and model rollback mechanisms.</li>
</ul>
<p><b>Collaboration with Risk DS</b></p>
<ul>
<li>Work closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.</li>
<li>Advise DS on efficient model architectures for operational environments.</li>
<li>Optimize feature computation for speed and scalability.</li>
</ul>
<p><b>System Design &amp; Integration</b></p>
<ul>
<li>Integrate models with credit underwriting, fraud detection, collections, and merchant risk systems.</li>
<li>Collaborate with backend engineering to align on API contracts and system interfaces.</li>
</ul>
<p><b>Your Expertise</b></p>
<ul>
<li>6+ years of experience as an MLE, ML Engineer, Mlops Developer.</li>
<li>Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).</li>
<li>Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).</li>
<li>Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).</li>
<li>Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).</li>
<li>Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).</li>
<li>Proven track record of deploying and maintaining ML models in production at scale.</li>
<li>Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).</li>
</ul>
<p>All qualified individuals are encouraged to apply.</p></div>

Machine Learning Engineer

Kforce Inc

<div>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 Kforce has a client that is seeking a Machine Learning Engineer in Los Angeles, CA.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Artificial Intelligence, Informatics or closely related field; Master's degree in computer science, engineering or closely related field preferred
  </li>
  <li>
   3 or more years relevant Machine Learning Engineer Experience
  </li>
  <li>
   Experience in managing end-to-end ML lifecycle
  </li>
  <li>
   Experience in managing automation with Terraform
  </li>
  <li>
   Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes)
  </li>
  <li>
   CI/CD tools (e.g., Github Actions)
  </li>
  <li>
   Programming languages and frameworks (e.g., Python, R, SQL)
  </li>
  <li>
   Deep understanding of coding, architecture, and deployment processes
  </li>
  <li>
   Strong understanding of critical performance metrics
  </li>
  <li>
   Extensive experience in predictive modeling, LLMs, and NLP
  </li>
  <li>
   Exhibit the ability to effectively articulate the advantages and applications of the RAG framework with LLMs
  </li>
  <li>
   Proven experience with: Artificial intelligence and machine learning platforms (e.g., AWS, Azure or GCP); Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes); CI/CD tools (e.g., GitHub Actions); Programming languages and frameworks (e.g., Python, R, SQL). MLOps engineering principles, agile methodologies, and DevOps life-cycle management; Technical writing and documentation for AI/ML models and processes; Healthcare data and machine learning use cases
  </li>
  <li>
   Healthcare Expertise: Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems
  </li>
  <li>
   Production Deployment and Model Engineering: Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability
  </li>
  <li>
   Scalable ML Infrastructures: Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Azure
   <br/>
   <br/>
  </li>
 </ul>
 The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
 <br/>
 <br/>
 We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability &amp; ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
 <br/>
 <br/>
 Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
 <br/>
 <br/>
 This job is not eligible for bonuses, incentives or commissions.
 <br/>
 <br/>
 Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
 <br/>
 <br/>
 By clicking &ldquo;Apply Today&rdquo; you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
</div>


Alignerr

<div>
 <strong>
  Machine Learning Engineer - AI Data Trainer
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Location: Remote
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 At Alignerr, we partner with the world&rsquo;s leading AI research teams and labs to build and train cutting-edge AI models.
 <br/>
 <br/>
 This initiative focuses on recording how an AI reasons and executes actions sequentially to handle practical assignments. Specialists draft precise, organized logs demonstrating strategizing, tool implementation, and choice-making, producing the data required to teach models to solve problems consistently in actual environments.
 <br/>
 <br/>
 <strong>
  Organization
 </strong>
 : Alignerr
 <strong>
  Position
 </strong>
 : Machine Learning Engineer - AI Data Trainer
 <strong>
  Type
 </strong>
 : Hourly Contract
 <strong>
  Compensation
 </strong>
 : $50&ndash;$70 /hour
 <strong>
  Location
 </strong>
 : Remote
 <strong>
  Commitment
 </strong>
 : 10&ndash;40 hours/week
 <br/>
 <br/>
 <strong>
  What You&rsquo;ll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Draft precise, organized logical logs for sophisticated technical challenges.
  </li>
  <li>
   Record sequential strategizing and choice-making workflows.
  </li>
  <li>
   Generate training datasets that illustrate proficient tool interaction for AI models.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Professional expertise in Machine Learning, Engineering, or a technical discipline.
  </li>
  <li>
   Superb skill in explaining intricate logical processes and methodologies clearly.
  </li>
  <li>
   Critical thinking skills to audit and refine AI-generated reasoning steps.
  </li>
  <li>
   Master's Degree or PhD
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Prior experience with data annotation, data quality, or evaluation systems.
  </li>
  <li>
   Master's Degree or PhD
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive pay and flexible remote work.
  </li>
  <li>
   Collaborate with a team working on cutting-edge AI projects.
  </li>
  <li>
   Exposure to advanced LLMs and how they&rsquo;re trained.
  </li>
  <li>
   Freelance perks: autonomy, flexibility, and global collaboration.
  </li>
  <li>
   Potential for contract extension.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Application Process (Takes 15-20 min)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Submit your resume
  </li>
  <li>
   Complete a short screening
  </li>
  <li>
   Project matching and onboarding
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 </em>
</div>


Keysight Technologies

<div>Overview:
<div>
Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.</div><div></div><div><br>
Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.</div><div></div><div><br>
We are seeking a Machine Learning Engineer to lead the design, development, and deployment of scalable machine learning models that power business decisions across the enterprise. This role combines technical depth in ML/AI with a strong understanding of business domains such as Sales, Service, Finance, Order Fulfillment, and Supply Chain. You will collaborate closely with Data Scientists, Data Engineers, and business partners to build production-ready solutions that drive measurable impact.</div>
Responsibilities:
<div>
1. Machine Learning Development &amp; Deployment</div><ul><li>
Design and implement supervised and unsupervised models for predictive analytics, including churn prediction, demand forecasting, renewal risk scoring, and cross-sell/upsell opportunity identification.</li><li>
Translate business problems into ML frameworks and production solutions that improve efficiency, revenue, or customer experience.</li><li>
Build, optimize, and maintain ML pipelines using tools such as MLflow, Airflow, or Kubeflow.</li></ul><div>
2. Cross-Functional ML Use Cases</div><ul><li>
Partner with teams across Sales (e.g., lead scoring, next-best action), Customer Service (e.g., case deflection, sentiment analysis), Finance (e.g., revenue forecasting, fraud detection), Supply Chain (e.g., inventory optimization, ETA prediction), and Order Fulfillment (e.g., delivery risk modeling) to define impactful ML use cases.</li><li>
Develop domain-specific models and continuously improve them using feedback loops and real-world performance data.</li></ul><div>
3. Model Governance and MLOps</div><ul><li>
Ensure robust model monitoring, versioning, and retraining strategies to keep models reliable in dynamic environments.</li><li>
Work closely with DevOps and Data Engineering teams to automate deployment, CI/CD workflows, and cloud-native ML infrastructure (AWS/GCP/Azure).</li></ul><div>
4. Data Engineering and Feature Architecture</div><ul><li>
Collaborate with data engineers to define feature stores, data quality checks, and model-ready datasets on platforms like Snowflake or Databricks.</li><li>
Perform feature selection, transformation, and engineering aligned with each domain&rsquo;s business logic.</li></ul><div>
5. Communication &amp; Stakeholder Collaboration</div><ul><li>
Present technical insights and model results to business and executive stakeholders in a clear, actionable format.</li><li>
Work with Product Owners and Program Managers to scope, prioritize, and plan delivery of ML projects.</li></ul>
Qualifications:
<div>
Required:</div><ul><li>
4-6 years of experience in machine learning, data science, or AI engineering, with a strong software engineering foundation.</li><li>
Proficiency in Python, and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.</li><li>
Experience deploying models into production using ML pipelines and orchestration frameworks.</li><li>
Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).</li></ul><div>
Preferred:</div><ul><li>
Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.</li><li>
Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).</li><li>
Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).</li><li>
Background in statistics, forecasting, optimization, or recommendation systems.</li></ul><div>
#LI-MO1</div><div></div><div><br>
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***</div><div></div><div><b><br>
California Pay range</b>: <b>MIN $145,970.00 - MAX $266,930.00</b></div><div><b>
Colorado pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
District of Columbia pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
Hawaii pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
Illinois pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
Maryland pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
Massachusetts pay range: MIN $145,970.00 - MAX $243,280.00</b></div><div><b>
Minnesota pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
New Jersey City pay range: MIN $145,970.00 - MAX $243,280.00
</b></div><div><b>New York pay range: MIN $160,160.00 - MAX $266,930.00</b></div><div><b>
Vermont pay range: MIN $135,150.00- MAX $225,250.00</b></div><div><b>
Washington state pay range: MIN $145,970.00 - MAX $243,280.00</b></div><div><br>
</div><div><b>Note:</b> For other locations, pay ranges will vary by region</div><div></div><div><br>
US Employees may be eligible for the following benefits:</div><ul><li>
Medical, dental and vision</li><li>
Health Savings Account</li><li>
Health Care and Dependent Care Flexible Spending Accounts</li><li>
Life, Accident, Disability insurance</li><li>
Business Travel Accident and Business Travel Health</li><li>
401(k) Plan</li><li>
Flexible Time Off, Paid Holidays</li><li>
Paid Family Leave</li><li>
Discounts, Perks</li><li>
Tuition Reimbursement</li><li>
Adoption Assistance</li><li>
ESPP (Employee Stock Purchase Plan)</li><li>
Restricted Stock Units</li></ul></div>

Skild AI

<div>
 <strong>
  Company Overview
 </strong>
 <p>
  At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
 </p>
 <strong>
  Position Overview
 </strong>
 <p>
  We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
 </p>
 <strong>
  Responsibilities
 </strong>
 <ul>
  <li>
   Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  </li>
  <li>
   Design and conduct experiments to train RL models and conduct real-world tests.
  </li>
  <li>
   Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  </li>
  <li>
   Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  </li>
  <li>
   Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  </li>
  <li>
   Stay up-to-date with the latest research and advancements in reinforcement learning.
  </li>
 </ul>
 <strong>
  Preferred Qualifications
 </strong>
 <ul>
  <li>
   BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  </li>
  <li>
   Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  </li>
  <li>
   Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  </li>
  <li>
   Strong background in algorithms, data structures, and software engineering principles.
  </li>
  <li>
   Experience with physics simulation engines and tools for training RL.
  </li>
  <li>
   Deep understanding of state-of-the-art machine learning techniques and models.
  </li>
  <li>
   Extensive industry experience with reinforcement learning and robotic systems.
  </li>
 </ul>
 <p>
  &nbsp;
 </p>
 <p>
  Base Salary Range: $100,000 USD - $300,000 USD
 </p>
</div>


Viettals Digital

<p>Job Opportunity: AI/Machine Learning Engineer</p><p><b>Location:</b> Kuwait City, Kuwait<br/><b>Company:</b> Viettals Digital</p><p>About Us</p><p>Viettals Digital is a forward-looking technology company dedicated to harnessing artificial intelligence and machine learning to drive innovation across industries. With a strong presence in Kuwait, we deliver intelligent solutions that empower businesses to optimize operations, enhance customer experiences, and achieve sustainable growth. To strengthen our engineering team, we are seeking a skilled <b>AI/Machine Learning Engineer</b> to design, build, and deploy advanced AI systems.</p><p>Role Overview</p><p>The <b>AI/Machine Learning Engineer</b> will be responsible for developing machine learning models, implementing AI solutions, and ensuring scalability and performance across applications. This role requires technical expertise, creativity, and the ability to collaborate with cross-functional teams to deliver impactful solutions.</p><p>Key Responsibilities</p><ul><li>Design, develop, and deploy machine learning models and AI solutions.</li><li>Collaborate with data scientists, engineers, and product teams to define requirements.</li><li>Implement algorithms for natural language processing, computer vision, and predictive analytics.</li><li>Optimize models for performance, scalability, and accuracy.</li><li>Ensure compliance with data governance, security, and ethical AI standards.</li><li>Monitor system performance and recommend improvements.</li><li>Stay updated on emerging AI/ML frameworks, tools, and industry trends.</li><li>Provide technical leadership and mentor junior engineers.</li></ul><p>Qualifications</p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, or related field.</li><li>5+ years of experience in AI/ML engineering, with hands-on expertise in model development and deployment.</li><li>Strong knowledge of Python, TensorFlow, PyTorch, and scikit-learn.</li><li>Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).</li><li>Familiarity with big data tools (Spark, Hadoop) and data pipelines.</li><li>Excellent analytical, organizational, and communication skills.</li><li>Ability to manage multiple priorities in a dynamic environment.</li><li>Fluency in English; Arabic is a strong advantage.</li></ul><p>Why Join Us?</p><ul><li>Be part of a respected digital innovation company shaping AI adoption in Kuwait.</li><li>Lead high-impact AI/ML initiatives with regional and international exposure.</li><li>Competitive salary and benefits package.</li><li>Opportunities for professional growth and career advancement.</li><li>Collaborative, innovative, and future-focused work culture.</li></ul><p>Pay: Up to KD2,800.000 per month</p><p>Work Location: In person</p>

AI/Machine Learning Engineer

Unifonic

<div>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 Proudly voted a Great Place to Work&reg;, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
 <br/>
 <br/>
 We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we&rsquo;re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
 <br/>
 <br/>
 <strong>
  Meet the team!
  <br/>
  <br/>
 </strong>
 Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic&rsquo;s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.
 <br/>
 <br/>
 As a Senior Machine Learning (AI) Engineer, you will be responsible for designing, developing, and deploying advanced machine learning solutions across various domains, including NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies.
 <br/>
 <br/>
 <strong>
  Help Us Shape The Future Of Communication By
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
  </li>
  <li>
   Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content.
  </li>
  <li>
   Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
  </li>
  <li>
   Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search).
  </li>
  <li>
   Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches.
  </li>
  <li>
   Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products.
  </li>
  <li>
   Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
  </li>
  <li>
   Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI).
  </li>
  <li>
   Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode.
  </li>
  <li>
   Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
  </li>
  <li>
   Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
  </li>
  <li>
   Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture.
  </li>
  <li>
   Assisting in the project documentation and demos.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Job Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  What you'll bring:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies (e.g., BM25, dense retrieval, hybrid approaches) and knowledge graph integration.
  </li>
  <li>
   Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
  </li>
  <li>
   Deep expertise in various NLP techniques and models, including but not limited to:
   <br/>
   <br/>
  </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 <br/>
 <br/>
 Large Language Models (LLMs) and their fine-tuning/adaptation
 <br/>
 <br/>
 Vector embeddings and similarity search
 <br/>
 <br/>
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 <br/>
 <br/>
 <ul>
  <li>
   Hands-on 3-5 years of relevant work experience as a Machine Learning Engineer.
  </li>
  <li>
   Hands-on 3+ years of experience with Python.
  </li>
  <li>
   Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
  </li>
  <li>
   End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
  </li>
  <li>
   Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modeling
  </li>
  <li>
   Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
  </li>
  <li>
   Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.
  </li>
  <li>
   Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
  </li>
  <li>
   Basic knowledge of Kubernetes and Docker is nice to have.
  </li>
  <li>
   Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
  </li>
  <li>
   Experience with the Hugging Face libraries (i.e. transformers).
  </li>
  <li>
   Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
  </li>
  <li>
   Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
  </li>
  <li>
   Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
  </li>
  <li>
   Familiar with Agile methodologies i.e. scrum and kanban.
  </li>
  <li>
   Ability to develop high-level architecture and low-level design, End-to-end for a specific project.
  </li>
  <li>
   Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is a plus.
  </li>
  <li>
   Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques is nice to have.
  </li>
  <li>
   Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is nice to have.
  </li>
  <li>
   General knowledge of Data warehouse tools e.g. Vertica is a plus.
  </li>
  <li>
   A Bachelor&rsquo;s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Software, etc).
  </li>
  <li>
   Excellent communication and collaboration skills.
  </li>
  <li>
   Good level of spoken and written Arabic and English.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  As a Unifone you will receive a range of benefits:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and bonus.
  </li>
  <li>
   Unifonic share scheme (we are all owners!).
  </li>
  <li>
   30 holiday days after the first anniversary.
  </li>
  <li>
   Your Birthday off!
  </li>
  <li>
   Spend up to 25 days per year working from anywhere in the world!
  </li>
  <li>
   Paid leave for new parents.
  </li>
  <li>
   LinkedIn learning license.
  </li>
 </ul>
</div>


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