machine learning engineer

TMC Middle East

<div>
 
 
 About the Role:
 
 
 
 We are looking for a Senior Machine Learning Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.
 
 
 
 
 
 
 What You'll Do:
 
 
 <ul>
 <li>
 Design, build, and scale machine learning models and infrastructure.
 </li>
 <li>
 Deploy deep learning and generative models into production for public and private sector projects.
 </li>
 <li>
 Collaborate with data scientists, product managers, and stakeholders to deliver AI-driven insights.
 </li>
 <li>
 Optimize ML training and inference for performance, latency, and scalability.
 </li>
 <li>
 Monitor, retrain, and improve deployed ML models.
 </li>
 <li>
 Drive consultation efforts, providing expert guidance to client stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science or related field.
 </li>
 <li>
 4+ years of experience in ML engineering, data science, and generative AI.
 </li>
 <li>
 Strong track record of projects across public and private sectors.
 </li>
 <li>
 Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks.
 </li>
 <li>
 Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama).
 </li>
 <li>
 Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices.
 </li>
 <li>
 Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services.
 </li>
 <li>
 Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science).
 </li>
 <li>
 Familiarity with MLOps practices and automation pipelines.
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer

Comprehensive Rehab Consultants

About Comprehensive Rehab Consultants (CRC)Comprehensive Rehab Consultants partners with skilled nursing facilities to improve clinical quality, efficiency, and financial performance. CRC is recognized as an innovator in the post-acute care space, developing new AI-driven care and revenue models that decrease hospitalizations and improve outcomes.We are seeking a Machine Learning Engineer to drive the next generation of CRC&rsquo;s AI platform. This role is engineering-heavy, focused on building, tuning, and deploying scalable ML/NLP/LLM systems that power our clinician tools, financial analytics, contract modeling, DFS/PDPM engines, readmission risk scores, and enterprise analytics chatbot.Role SummaryYou will design, optimize, and productionize machine learning systems using CRC&rsquo;s full internal data environment. This includes tuning an existing NLP engine, developing statistical/ML models (including ordered probit and regression-based DFS calculator), building internal LLMs trained on CRC documents, and developing the AI analytics chatbot used by all business units.This role requires someone who ships ML systems&mdash;not someone who just builds notebooks.Key ResponsibilitiesMachine Learning &amp; Statistical Modeling<ul><li>Build, tune, and validate statistical models including multi-stage regression, ordered probit, and generalized linear models, audit automation, acuity scoring, and financial forecasting</li><li>Engineer features from structured and unstructured healthcare data (EMR, claims, revenue cycle, clinician notes)</li></ul>NLP &amp; LLM Engineering<ul><li>Tune the existing CRC NLP engine for clinical note understanding, keyword extraction, concept expansion, negation detection, and sentiment scoring</li><li>Build custom clinical embeddings using HuggingFace Transformers, spaCy, and domain-tuned vector models</li><li>Develop and maintain a CRC private LLM, trained on internal knowledge bases, documentation, analytics logic, and care guidelines</li><li>Build automated pipelines for LLM evaluation, retraining, retrieval-augmented generation (RAG), and grounded QA</li></ul>AI-Driven Product Development<ul><li>Architect, build, and deploy the AI Analytics Chatbot, integrating model logic, business rules, and Fabric/Databricks data sources</li><li>Integrate ML models into production services using notebooks, APIs, or batch inference jobs</li><li>Support creation of AI-generated reporting, insights summaries, and automated clinical/financial narratives</li></ul>MLOps &amp; Engineering<ul><li>Build maintainable ML pipelines (training, validation, deployment) using Databricks, Fabric, MLflow, GitHub, and CI/CD</li><li>Implement model monitoring, drift detection, and automated retraining</li><li>Package and deploy reproducible models via APIs or scheduled Fabric/Databricks workflows</li></ul>Collaboration &amp; Delivery<ul><li>Work with data engineering to embed models into CRC applications</li><li>Partner with BI analysts to transform model outputs into dashboards</li><li>Document methodologies, assumptions, architecture, and validation processes clearly</li></ul>Required Skills &amp; Experience<ul><li>3&ndash;6 years of hands-on machine learning engineering experience (not just DS notebooks)</li><li>Strong Python engineering background: pandas, scikit-learn, statsmodels, PyTorch or TensorFlow, transformers, spaCy</li><li>Experience building and tuning LLM and NLP pipelines end-to-end</li><li>Experience with regression, ordered probit/logit, hierarchical models, and general statistical modeling</li><li>Experience deploying ML workloads in Databricks, Azure ML, and Fabric</li><li>Strong SQL for feature engineering and model validation</li><li>Prior experience working with healthcare data (EMR, claims, RCM, CMS) preferred</li><li>Strong communication and the ability to explain complex ML systems to non-technical stakeholders.</li><li>Proactive, self-managing engineer who can independently own ML systems end-to-end.</li><li>Fluent English required</li></ul>Preferred Qualifications<ul><li>Experience with:</li><li>Retrieval-Augmented Generation (RAG) pipelines</li><li>Vector databases (FAISS, Chroma, Pinecone, Qdrant)</li><li>Enterprise chatbot frameworks</li><li>MLflow, CI/CD, GitHub Actions, and model versioning</li><li>Power BI integration for ML outputs</li><li>FHIR/SMART on FHIR</li></ul>Certifications considered:<ul><li>Databricks ML Associate/Professional</li><li>Azure AI Engineer Associate</li><li>DeepLearning.AI NLP/LLM specializations</li></ul>Job Type: Full-timePay: From Rs3,030,000.00 per yearExperience:<ul><li>hands-on machine learning engineering: 3 years (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>Work Location: Remote

About Comprehensive Rehab Consultants (CRC)Comprehensive Rehab Consultants partners with skilled nursing facilities to improve clinical quality, efficiency, and financial performance. CRC is recognized as an innovator in the post-acute care space, developing new AI-driven care and revenue models that decrease hospitalizations and improve outcomes.We are seeking a Machine Learning Engineer to drive the next generation of CRC&rsquo;s AI platform. This role is engineering-heavy, focused on building, tuning, and deploying scalable ML/NLP/LLM systems that power our clinician tools, financial analytics, contract modeling, DFS/PDPM engines, readmission risk scores, and enterprise analytics chatbot.Role SummaryYou will design, optimize, and productionize machine learning systems using CRC&rsquo;s full internal data environment. This includes tuning an existing NLP engine, developing statistical/ML models (including ordered probit and regression-based DFS calculator), building internal LLMs trained on CRC documents, and developing the AI analytics chatbot used by all business units.This role requires someone who ships ML systems&mdash;not someone who just builds notebooks.Key ResponsibilitiesMachine Learning &amp; Statistical Modeling<ul><li>Build, tune, and validate statistical models including multi-stage regression, ordered probit, and generalized linear models, audit automation, acuity scoring, and financial forecasting</li><li>Engineer features from structured and unstructured healthcare data (EMR, claims, revenue cycle, clinician notes)</li></ul>NLP &amp; LLM Engineering<ul><li>Tune the existing CRC NLP engine for clinical note understanding, keyword extraction, concept expansion, negation detection, and sentiment scoring</li><li>Build custom clinical embeddings using HuggingFace Transformers, spaCy, and domain-tuned vector models</li><li>Develop and maintain a CRC private LLM, trained on internal knowledge bases, documentation, analytics logic, and care guidelines</li><li>Build automated pipelines for LLM evaluation, retraining, retrieval-augmented generation (RAG), and grounded QA</li></ul>AI-Driven Product Development<ul><li>Architect, build, and deploy the AI Analytics Chatbot, integrating model logic, business rules, and Fabric/Databricks data sources</li><li>Integrate ML models into production services using notebooks, APIs, or batch inference jobs</li><li>Support creation of AI-generated reporting, insights summaries, and automated clinical/financial narratives</li></ul>MLOps &amp; Engineering<ul><li>Build maintainable ML pipelines (training, validation, deployment) using Databricks, Fabric, MLflow, GitHub, and CI/CD</li><li>Implement model monitoring, drift detection, and automated retraining</li><li>Package and deploy reproducible models via APIs or scheduled Fabric/Databricks workflows</li></ul>Collaboration &amp; Delivery<ul><li>Work with data engineering to embed models into CRC applications</li><li>Partner with BI analysts to transform model outputs into dashboards</li><li>Document methodologies, assumptions, architecture, and validation processes clearly</li></ul>Required Skills &amp; Experience<ul><li>3&ndash;6 years of hands-on machine learning engineering experience (not just DS notebooks)</li><li>Strong Python engineering background: pandas, scikit-learn, statsmodels, PyTorch or TensorFlow, transformers, spaCy</li><li>Experience building and tuning LLM and NLP pipelines end-to-end</li><li>Experience with regression, ordered probit/logit, hierarchical models, and general statistical modeling</li><li>Experience deploying ML workloads in Databricks, Azure ML, and Fabric</li><li>Strong SQL for feature engineering and model validation</li><li>Prior experience working with healthcare data (EMR, claims, RCM, CMS) preferred</li><li>Strong communication and the ability to explain complex ML systems to non-technical stakeholders.</li><li>Proactive, self-managing engineer who can independently own ML systems end-to-end.</li><li>Fluent English required</li></ul>Preferred Qualifications<ul><li>Experience with:</li><li>Retrieval-Augmented Generation (RAG) pipelines</li><li>Vector databases (FAISS, Chroma, Pinecone, Qdrant)</li><li>Enterprise chatbot frameworks</li><li>MLflow, CI/CD, GitHub Actions, and model versioning</li><li>Power BI integration for ML outputs</li><li>FHIR/SMART on FHIR</li></ul>Certifications considered:<ul><li>Databricks ML Associate/Professional</li><li>Azure AI Engineer Associate</li><li>DeepLearning.AI NLP/LLM specializations</li></ul>Job Type: Full-timePay: From &#8377;949,364.77 per yearBenefits:<ul><li>Paid time off</li></ul>Experience:<ul><li>hands-on machine learning engineering: 3 years (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>

Rough Copies Pvt Ltd

Location: Johar Town, Lahore Timing: 7 PM &ndash; 2 AMAbout the Role: We are hiring a Machine Learning Engineer with hands-on experience in Recommendation Systems and TensorFlow. You will design, train, and deploy ML models, optimize pipelines, and work on real-world AI applications.Key Responsibilities:<ul><li>Build and optimize recommendation systems (collaborative/content-based)</li><li>Develop ML models using TensorFlow</li><li>Integrate ML models into production pipelines</li><li>Collaborate with cross-functional teams and deliver results on time</li></ul>Requirements:<ul><li>2&ndash;3 years of professional ML experience</li><li>Strong Python, NumPy, Pandas skills</li><li>Experience with TensorFlow and model deployment</li><li>Knowledge of recommendation systems</li><li>Ability to work independently in a night shift environment</li></ul>Preferred:<ul><li>API integration experience</li><li>Experience with real-time ML systems</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Do you have experience building recommendation systems?</li><li>Have you worked with TensorFlow for model building and deployment?</li></ul>Experience:<ul><li>Machine Learning : 2 years (Required)</li></ul>Work Location: In person

AxcelerateAI

We are a software development company with a strong specialised focus on developing artificial intelligence-based solutions for real-world industrial problems. We focus on using state-of-the-art AI technologies to solve complex industrial problems.We are looking for a Machine Learning (ML) engineer, with a specialisation in deep learning, to join our team.Position DetailsType: Full-timeLocation: In-person, Johar Town LahoreJob DescriptionCoordinating with an in-house or external data team to design a strategy for collecting appropriate data for building a deep learning model for the required taskDesigning, building and training deep learning models using state-of-the-art architectures including CNNs, LSTMs, attention networks and transformers. Training is either done on our on-premise servers or on the cloud (e.g., using AWS servers)Deploying the final model on a server and providing an interface or APIs to interact with itMinimum RequirementsBachelor&rsquo;s or Master&rsquo;s degree in EE, CS or Data ScienceAbility to formulate a problem as a machine learning problemA reasonable theoretical/mathematical understanding of various deep learning architecturesA reasonable theoretical/mathematical understanding of various objective/loss functionsStrong programming skills in PythonExtensive experience in either TensorFlow or PyTorchPrior experience of using deep learning either in research or industrial settingNo minimum prior industry experience is needed if the candidate fulfills the above requirements.Job Type: Full-timeWork Location: In person

Envision Employment Solutions

Envision Employment Solutions is currently looking for a Machine Learning Engineer for one of our partners, a global leader in consulting, digital transformation, technology, and engineering services.
 
Responsibilities: 
<ul>
<li>Machine Learning & AI Solutions</li>
<li>Deploy advanced machine learning models and AI-driven solutions across cloud environments.</li>
<li>Lead the end-to-end lifecycle of ML models, from data ingestion and feature engineering to model training, evaluation, and deployment.</li>
<li>Monitor model performance and implement retraining strategies to ensure long-term accuracy and relevance.</li>
<li>Cloud & Data Engineering</li>
<li>Architect and optimize scalable data pipelines and cloud-based infrastructures (Azure, AWS, or GCP) to support ML workloads.</li>
<li>Collaborate with data engineers to ensure robust data preprocessing, transformation, and storage strategies.</li>
<li>MLOps & Automation</li>
<li>Develop and maintain CI/CD pipelines tailored for ML workflows, including automated testing, model versioning, and deployment.</li>
<li>Integrate monitoring and alerting systems to track model drift, data quality, and system performance.</li>
<li>Collaboration & Innovation</li>
<li>Work closely with cross-functional teams including data scientists, product managers, and business stakeholders to translate business needs into technical solutions.</li>
<li>Mentor junior engineers and contribute to knowledge sharing and best practices across the team.</li>
</ul>
Requirements: 
<ul>
<li>Technical Skills</li>
<li>Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).</li>
<li>Strong command of SQL and experience with large-scale data processing tools (e.g., Spark, Pandas).</li>
<li>Deep understanding of cloud platforms (Azure, AWS, GCP) and their ML services.</li>
<li>Skilled in MLOps practices, including CI/CD, containerization (Docker), and orchestration (Kubernetes).</li>
<li>Familiarity with Git and collaborative development workflows.</li>
<li>Experience</li>
<li>6+ years of experience working with complex datasets and solving real-world business problems using AI</li>
<li>Proven track record of deploying and maintaining ML models in production environments.</li>
<li>Communication Skills</li>
<li>Excellent written and verbal communication skills to collaborate effectively with cross-functional teams.</li>
<li>Fluent in Qatari Arabic & English, both spoken and written.</li>
<li>Additional Skills</li>
<li>Strong problem-solving abilities and attention to detail.</li>
<li>Ability to work collaboratively in a team environment.</li>
<li>Self-motivated with a continuous learning mindset.</li>
<li>Team management.</li>
</ul>
Benefits: 
<ul>
<li>Competitive Salary based on experience</li>
<li>Social and medical insurance</li>
<li>Learning, development and career progression</li>
</ul>

Itron

<div><div>Itron is innovating new ways for utilities and cities to manage energy and water. We create a more resourceful world to protect essential resources for today and tomorrow. Join us.</div><div></div><div>
Itron's Resiliency Solutions business helps make communities more adaptive and sustainable. We do this by pairing external data with artificial intelligence to identify areas of high risk and prevent catastrophic loss for utilities and critical infrastructure owners across the country. We are a team of close-knit engineers, subject matter experts, and business leaders who obsess over problem-solving, new technologies, and making a positive impact in our communities.</div><div></div><div>
Title: Machine Learning Engineer</div><div>
Location: Bangalore.</div><div>
About the Role 
We are looking for a Machine Learning Engineer to join our data and AI engineering team. In this role, you&rsquo;ll help design, build, and maintain end-to-end machine learning systems &mdash; from data pipelines to model deployment and monitoring. This position is ideal for someone who enjoys working at the intersection of software engineering and applied machine learning, and who wants to see their models perform at scale in production environments.</div><div>
What You&rsquo;ll Do 
<ul><li>Collaborate with data scientists and product teams to productionize machine learning models and ensure scalability, reliability, and performance.</li><li>Design, build, and maintain data pipelines to support model training and inference using tools like Spark, Airflow, or Kubeflow.</li><li>Implement model serving infrastructure, APIs, and CI/CD workflows for automated model deployment and updates.</li><li>Optimize model performance for latency, throughput, and cost efficiency in production environments.</li><li>Integrate ML solutions into applications and services, working closely with software engineers.</li><li>Monitor and maintain ML systems to ensure data integrity, model drift detection, and reliable predictions.</li><li>Contribute to MLOps best practices &mdash; including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow, Weights &amp; Biases).</li><li>Collaborate on architecture design for scalable ML systems on cloud platforms (AWS, GCP, Azure).</li><li>Stay current with advances in ML systems, frameworks, and cloud technologies.</li></ul></div><div>
Who You Are 
<ul><li>Education: Bachelor&rsquo;s, Master&rsquo;s, or PhD in Computer Science, Engineering, or a related technical field.</li><li>Experience:</li><li>Level I: 1&ndash;3 years of experience building or deploying ML models.</li><li>Proficient in programming languages such as Python or Java, with experience in ML libraries like TensorFlow, PyTorch, or scikit-learn.</li><li>Strong software engineering skills &mdash; clean, modular code; version control (Git); testing; and documentation.</li><li>Experience with data infrastructure (SQL, Spark, Kafka, Airflow, or similar).</li><li>Hands-on experience with containerization and orchestration (Docker, Kubernetes).</li><li>Familiarity with CI/CD pipelines for ML deployment (Jenkins, GitHub Actions, etc.).</li><li>Cloud experience with AWS SageMaker, GCP Vertex AI, or Azure ML is highly preferred.</li><li>Understanding of MLOps concepts, model monitoring, and lifecycle management.</li><li>Strong problem-solving, debugging, and communication skills.</li></ul></div><div></div><div>
Itron is committed to building an inclusive and diverse workforce and providing an authentic workplace experience for all employees. If you are excited about this role but your past experiences don't perfectly align with every requirement, we encourage you to apply anyway. In the end, you may be just who we are looking for! 
 
The successful candidate's starting wage will be determined based on permissible, non-discriminatory factors such as skills and experience. 
 
Itron is proud to be an Equal Opportunity Employer. If you require an accommodation to apply, please contact a recruiting representative at 1-800-635-5461 or email <div>Accessibility@itron.com</div>.</div><div> 
Itron is transforming how the world manages energy, water and city services. Our trusted intelligent infrastructure solutions help utilities and cities improve efficiency, build resilience and deliver safe, reliable and affordable service. With edge intelligence, we connect people, data insights and devices so communities can better manage the essential resources they rely on to live. Join us as we create a more resourceful world: <div>www.itron.com</div></div></div><div></div>

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