machine learning engineer

RITS

<p><b>Machine Learning Engineer</b></p><p><b>Role Summary:</b><br/>Responsible for designing, developing, and deploying machine learning models and data-driven solutions.</p><p><b>Key Responsibilities:</b></p><ul><li>Build, train, and optimize ML models and algorithms.</li><li>Work with large datasets, preprocessing, feature engineering, and data pipelines.</li><li>Deploy ML models into production environments.</li><li>Collaborate with data engineers, software developers, and product teams.</li><li>Monitor model performance and retrain when required.</li></ul><p><b>Requirements:</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s in Computer Science, AI, Data Science, or related field.</li><li>Strong knowledge of Python, TensorFlow/PyTorch, Scikit-learn.</li><li>Experience with APIs, model deployment, and cloud platforms (AWS/Azure/GCP).</li><li>Good understanding of statistics, NLP, or computer vision (optional).</li></ul><p>Job Types: Full-time, Permanent</p><p>Application Question(s):</p><ul><li>What is your expected salary?</li><li>What is your earliest availability to join?</li></ul><p>Education:</p><ul><li>Bachelor's (Required)</li></ul><p>Experience:</p><ul><li>Machine Learning Engineer: 3 years (Preferred)</li><li>knowledge of Python, TensorFlow/PyTorch, Scikit-learn: 2 years (Preferred)</li></ul><p>Location:</p><ul><li>Doha (Required)</li></ul>

Machine Learning Engineer

Experts Group International

<div>
 <p>
  *This is a 12 month contract*
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Position Title:
  </strong>
  Machine Learning Engineer (12 month contract)
 </p>
 <p>
  <strong>
   Reports to:
  </strong>
  Senior Manager, Data &amp; AI
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   JOB PURPOSE
  </strong>
 </p>
 <p>
  The Machine Learning Engineer will play a key role in developing and deploying production-grade AI/ML models that support critical business processes such as decision automation, customer analytics, and intelligent operations. The role is responsible for embedding machine learning into scalable, real-time workflows across the organisation.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   CORE RESPONSIBILITIES
  </strong>
 </p>
 <p>
  <strong>
   Model Engineering &amp; Optimization
  </strong>
 </p>
 <ul>
  <li>
   Deploy and maintain machine learning models in production environments with strong focus on performance, scalability, and reliability.
  </li>
  <li>
   Optimize ML pipelines for low-latency and real-time inference use cases.
  </li>
  <li>
   Integrate explainability frameworks (e.g., SHAP) into dashboards and business tools.
  </li>
 </ul>
 <p>
  <strong>
   Data Pipeline Development
  </strong>
 </p>
 <ul>
  <li>
   Design and build scalable ETL/ELT pipelines using Databricks, Python, and SQL for ingesting data from CRM, ERP, and third-party systems.
  </li>
  <li>
   Ensure data quality, consistency, and timely availability for ML models and business intelligence platforms.
  </li>
  <li>
   Monitor and troubleshoot data pipelines to reduce downtime and support reporting needs.
  </li>
 </ul>
 <p>
  <strong>
   MLOps &amp; Model Lifecycle Management
  </strong>
 </p>
 <ul>
  <li>
   Implement CI/CD pipelines for machine learning using tools such as MLflow, DVC, or SageMaker Pipelines.
  </li>
  <li>
   Maintain version control, reproducibility, and consistent deployments across staging and production environments.
  </li>
  <li>
   Conduct model validation, A/B testing, drift detection, and ongoing model performance monitoring.
  </li>
 </ul>
 <p>
  <strong>
   Collaboration &amp; Communication
  </strong>
 </p>
 <ul>
  <li>
   Work closely with data scientists to productionize model prototypes for optimal performance and stability.
  </li>
  <li>
   Act as the link between technical teams and business stakeholders to integrate ML outputs into daily operations.
  </li>
  <li>
   Present insights, findings, and project updates in clear, actionable formats tailored to both technical and non-technical audiences.
  </li>
 </ul>
 <p>
  <strong>
   Training, Support &amp; Documentation
  </strong>
 </p>
 <ul>
  <li>
   Create and maintain documentation for ML models, pipelines, and workflows.
  </li>
  <li>
   Provide training to analysts and end-users on interpreting model outputs, risk scores, and key performance indicators.
  </li>
  <li>
   Support ad-hoc data requests and contribute to analysis involving integrated ML components.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   QUALIFICATIONS &amp; EXPERIENCE
  </strong>
 </p>
 <p>
  <strong>
   Education
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Engineering, Data Science, Operations Research, Statistics, Applied Mathematics, or a related field (equivalent experience considered).
  </li>
 </ul>
 <p>
  <strong>
   Technical Skills
  </strong>
 </p>
 <ul>
  <li>
   Strong experience across the full machine learning lifecycle including data preprocessing, model development, evaluation, deployment, and monitoring.
  </li>
  <li>
   Proficiency in
   <strong>
    Python
   </strong>
   ,
   <strong>
    SQL
   </strong>
   , and ML libraries (scikit-learn, XGBoost, TensorFlow, PyTorch).
  </li>
  <li>
   Hands-on experience with
   <strong>
    MLOps platforms
   </strong>
   (MLflow, SageMaker, Azure ML, Databricks Model Serving).
  </li>
  <li>
   Familiarity with CI/CD for ML,
   <strong>
    Docker
   </strong>
   , and orchestration tools (Airflow, Kubeflow, etc.).
  </li>
 </ul>
 <p>
 </p>
</div>


Radiance Technologies Inc.

<div><div>Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection. Additionally, this position will improve upon current methods for the automated processing and exploitation of large data sets. This will include R&amp;D on projects involving the exploitation of data from sensors including investigation of state-of-the-art machine learning classification methods to detect, track, and characterize targets of interest.</div><div></div><div>
Radiance Technologies is an employee-owned company with benefits that are unmatched by most companies in the Dayton OH area. Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, interesting assignments, educational reimbursement, competitive salaries and a pleasant work environment combine to make Radiance Technologies a great place to work and succeed.</div><div></div><div>
Required Experience:</div><ul><li><div>
A working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)</div></li><li><div>
Experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Decision Trees, Dimensional Reduction, Neural Networks &amp; Deep Learning, Feature Engineering</div></li></ul><div></div><div><br>
Required Skills &amp; Qualifications:</div><ul><li><div>
Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, Statistics, or a related field</div></li><li><div>
Strong programming skills in at least one of the following languages Python, Matlab, C++</div></li><li><div>
Experience with Machine Learning APIs, such as TensorFlow, PyTorch, or Keras</div></li><li><div>
Active Secret Clearance with ability to obtain and maintain a TS/SCI</div></li></ul><div></div><div>
Desired Skills:</div><ul><li><div>
ML for either natural language processing, computer vision, reinforcement learning, generative modeling, or equivalent experience</div></li><li><div>
PhD in data science, mathematics, statistics, computer science, a physical science or engineering is strongly desired</div></li><li><div>
A mathematical background (Probability and Statistics)</div></li><li><div>
An experienced grasp of version control using Git for nonlinear workflows</div></li><li><div>
Thorough understanding of working in research, development and production environments</div></li><li><div>
Background in image science, imagery exploitation, spatial analysis, and computer vision are a plus</div></li><li><div>
R&amp;D on remotely sensed data to include modeling and development of algorithms.</div></li><li><div>
Ability to work independently or in a team environment</div></li><li><div>
Strong technical writing and oral communication skills</div></li><li><div>
Active Top Secret/SCI clearance</div></li></ul><div></div><div>
EOE/Minorities/Females/Vet/Disabled</div></div>

Comprehensive Rehab Consultants

<p><b>About Comprehensive Rehab Consultants (CRC)</b></p><p>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.</p><p>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.</p><p><b>Role Summary</b></p><p>You 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.</p><p>This role requires someone who ships ML systems&mdash;not someone who just builds notebooks.</p><p><b>Key Responsibilities</b></p><p><b>Machine Learning &amp; Statistical Modeling</b></p><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><p><b>NLP &amp; LLM Engineering</b></p><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><p><b>AI-Driven Product Development</b></p><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><p><b>MLOps &amp; Engineering</b></p><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><p><b>Collaboration &amp; Delivery</b></p><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><p><b>Required Skills &amp; Experience</b></p><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><p><b>Preferred Qualifications</b></p><ul><li><b>Experience with:</b></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><p>Certifications considered:</p><ul><li>Databricks ML Associate/Professional</li><li>Azure AI Engineer Associate</li><li>DeepLearning.AI NLP/LLM specializations</li></ul><p>Job Type: Full-time</p><p>Pay: From Rs3,030,000.00 per year</p><p>Experience:</p><ul><li>hands-on machine learning engineering: 3 years (Preferred)</li></ul><p>Language:</p><ul><li>English (Preferred)</li></ul><p>Work Location: Remote</p>

Rough Copies Pvt Ltd

<p><b>Location:</b> Johar Town, Lahore<br/><b>Timing:</b> 7 PM &ndash; 2 AM</p><p><b>About the Role:</b><br/>We are hiring a <b>Machine Learning Engineer</b> with hands-on experience in <b>Recommendation Systems</b> and <b>TensorFlow</b>. You will design, train, and deploy ML models, optimize pipelines, and work on real-world AI applications.</p><p><b>Key Responsibilities:</b></p><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><p><b>Requirements:</b></p><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><p><b>Preferred:</b></p><ul><li>API integration experience</li><li>Experience with real-time ML systems</li></ul><p>Job Type: Full-time</p><p>Application Question(s):</p><ul><li>Do you have experience building recommendation systems?</li><li>Have you worked with TensorFlow for model building and deployment?</li></ul><p>Experience:</p><ul><li>Machine Learning : 2 years (Required)</li></ul><p>Work Location: In person</p>

YO IT CONSULTING

<div><div><div>Position Overview
</div></div><div><div>As a MLE-2, you will design, implement, and optimize AI solutions while ensuring model success. You will lead the ML lifecycle from development to deployment, collaborate with cross-functional teams, and enhance AI capabilities to drive innovation and impact.
</div>
</div><div></div><div><div>Key Responsibilities:
</div></div><div><div>Design and implement AI product features.
</div><div>Maintain and optimize existing AI systems.
</div><div>Train, evaluate, deploy, and monitor ML models.
</div><div>Design ML pipelines for experiment, model, and feature management.</div>
<div>Implement A/B testing and scalable model inferencing APIs.
</div><div>Optimize GPU architectures, parallel training, and fine-tune models for improved performance.</div>
<div>Deploy LLM solutions tailored to specific use cases.
</div><div>Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks.</div>
</div>
<div></div><div><div>Technical Requirements:
</div></div><div><div>LLM &amp; ML: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama
</div><div>LLMOps: MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI
</div><div>Databases: MongoDB, PostgreSQL, Pinecone, ChromDB</div>
<div>Cloud: AWS, Azure
</div><div>DevOps: Kubernetes, Docker</div>
<div>Languages: Python, SQL, JavaScript
</div><div>Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert</div>
</div>
<div></div><div><div>What You'll Do:
</div></div><div><div>Collaborate with cross-functional teams to design and build scalable ML solutions.
</div><div>Implement state-of-the-art ML techniques, including NLP, Generative AI, RAG, and Transformer architectures.
</div><div>Deploy and monitor ML models for high performance and reliability.
</div><div>Innovate through research, staying ahead of industry trends.
</div><div>Build scalable data pipelines following best practices.
</div><div>Present key insights and drive decision-making.</div>
</div>
<div></div><div><div>What You Need to Succeed:
</div></div><div><div>Master&rsquo;s degree or equivalent experience in Machine Learning.
</div><div>3+ years of industry experience in ML, software engineering, and data engineering.</div>
<div>Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
</div><div>Strong programming skills in Python and JavaScript.
</div><div>Hands-on experience with ML Ops practices.
</div><div>Ability to work with research and product teams.</div>
<div>Excellent problem-solving skills and a track record of innovation.
</div><div>Passion for learning and applying the latest technological advancements.</div></div></div>

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.
<br><br>
<b>Responsibilities:</b><br>
<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>
<b>Requirements:</b><br>
<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>
<b>Benefits:</b><br>
<ul>
<li>Competitive Salary based on experience</li>
<li>Social and medical insurance</li>
<li>Learning, development and career progression</li>
</ul>


Search 10000+ Machine learning engineer jobs near you this December. New roles added regularly across leading industries. Apply today.

10000 machine learning engineer jobs NEAR_ME

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer