sales engineer

mechanical engineer

qa engineer

ai engineer

electrical engineer

ml engineer

SARJ

<div>Sarj.ai is hiring an AI/ML Engineer to train and deploy speech models that power our voice communications platform. We work in Python and PyTorch on GCP. Strong deep learning fundamentals highly appreciated.<h3 class="jobSectionHeader">
What you'll do</h3><ul><li>
Train large-scale speech models (STT/TTS)</li><li>
Work with modern speech architectures and push them to production</li><li>
Build and maintain ML training pipelines for real-time voice processing</li><li>
Develop evaluation frameworks and improve model performance</li><li>
Collaborate with product and engineering to ship AI-powered features</li></ul><h3 class="jobSectionHeader">
What we're looking for</h3><ul><li>
2+ years working with ML in production</li><li>
Strong Python + PyTorch/PyTorch Lightning</li><li>
Understanding of deep learning fundamentals</li><li>
Experience with speech/audio ML is a strong plus</li><li>
Experience with large-scale or distributed training</li><li>
Familiarity with GCP (Vertex AI, Cloud Run, BigQuery)</li></ul></div>

AI Research Engineer

MASTER-WORKS

<div>This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
<ul><li>Design, develop, train, and optimize machine learning models for real applications or use cases.</li><li>
Translate business and product requirements into scalable ML/AI solutions.
</li><li>Implement feature engineering, model selection, tuning, and evaluation techniques.
</li><li>Develop , and deploy ML models into production environments with high availability and performance.</li><li>
Build and maintain ML pipelines (training, validation, deployment, monitoring).
</li><li>Monitor model performance, data drift, and model decay; retrain models as needed.
</li><li>Ensure models meet reliability, scalability, and security standards.
</li><li>Work closely with Data Scientists, Product Managers, and Software Engineers.
</li><li>Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.</li><li>
Participate in design and code reviews, ensuring engineering best practices.
</li><li>Optimize models for latency, throughput, and cost.
</li><li>Implement experimentation frameworks (A/B testing, offline evaluation).
</li><li>Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul> 

Requirements 
<ul><li>
3&ndash;7+ years of hands-on experience in Machine Learning or applied AI roles.</li><li>
Strong programming skills in Python (and/or Java, Scala).
</li><li>Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
</li><li>Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
</li><li>Experience deploying models using Docker, Kubernetes, or cloud ML services.
</li><li>Strong knowledge of data structures, algorithms, and software engineering principles.
</li><li>Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
</li><li>Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
</li><li>Experience with big data technologies (Spark, Kafka, Databricks).
</li><li>Background in NLP, Computer Vision, or Generative AI.
</li><li>Strong problem-solving and analytical thinking
</li><li>Production-first mindset
</li><li>Data-driven decision making
</li><li>High Collaboration and communication skills</li></ul></div>

AI Engineer

Qualcomm

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Middle East Information Technology Company LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Software Test Engineering
General Summary:
About Us
<div>Qualcomm is growing its presence in Riyadh and is hiring Data Centre Engineers to support our expanding infrastructure across the region . As Saudi Arabia accelerates its digital transformation under Vision 2030, Qualcomm is investing in world‑class computing and data centre capabilities to power AI, cloud, and advanced connectivity at scale. This is a unique opportunity to work in a fast‑growing technology hub, supporting critical environments and helping shape the future of data centre operations in the Kingdom and beyond.
</div>About the Role
We are looking for a Site Reliability Engineer or Senior Engineer &ndash; Datacentre AI Engineering at Qualcomm Technologies, Inc., located in Riyadh, Saudi Arabia.
The role focuses on the design, operation, and continuous improvement of large‑scale AI inference systems in a datacenter environment. The engineer will support critical AI use cases by ensuring Qualcomm&rsquo;s AI infrastructure is reliable, scalable, and production‑ready for advanced machine‑learning workloads.
The role requires strong systems and software engineering fundamentals, hands‑on execution, and the ability to work independently on complex problem areas while collaborating closely with cross‑functional teams across hardware, software, and machine learning.
Ideal candidates will have 2-8 years of experience
Key Responsibilities will include
Key Responsibilities
1. AI Infrastructure
<ul><li>Design, deploy, and operate large‑scale AI inference systems supporting critical AI workloads.
</li><li>Ensure reliability, availability, and scalability of Qualcomm datacenter AI clusters.
</li><li>Develop and maintain software tools and support infrastructure around AI software stacks.
</li></ul>2. AI &amp; ML Engineering
<ul><li>Analyze software requirements and collaborate with architecture and hardware engineers to support AI workloads.
</li><li>Build, deploy, and operate components supporting LLM inference, agentic AI workflows, and AI services.
</li><li>Work with models, systems, and software teams to improve model performance on AI100 deployments.
</li><li>Identify and implement optimizations for workloads running on multi‑SoC and multi‑card systems.
</li></ul>3. Site Reliability Engineering (SRE)
<ul><li>Apply SRE fundamentals including monitoring, alerting, incident response, and performance optimization.
</li><li>Support production ML systems using MLOps tools and operational best practices.
</li><li>Contribute to incident reviews, operational documentation, and continuous reliability improvements.
</li></ul>4. Observability &amp; Tooling
<ul><li>Build and maintain observability tools, dashboards, and alerts to monitor system health and reliability.
</li><li>Monitor infrastructure and services using tools such as Prometheus, Grafana, CloudWatch, and custom telemetry.
</li><li>Create and maintain technical documentation, runbooks, and knowledge‑base articles.
</li></ul>5. Automation &amp; CI/CD
<ul><li>Develop automation to reduce manual operational tasks and improve system reliability.
</li><li>Support CI/CD pipelines for AI service and agent deployment.
</li><li>Apply Infrastructure‑as‑Code practices using tools such as Terraform and Ansible.
</li></ul><div></div>Required Skillset
1. AI &amp; Deep Learning
<ul><li>Experience working with AI/ML workloads such as LLMs, NLP, Vision, Audio, or Recommendation systems.
</li><li>Understand ML inference concepts including batching, token streaming, and performance considerations.
</li><li>Hands‑on experience with PyTorch and familiarity with modern ML frameworks.
</li><li>Familiarity with distributed inference, checkpointing, and accelerator‑based compute environments.
</li></ul>2. AI Operations
<ul><li>Experience supporting AI or ML applications in production environments.
</li><li>Familiarity with LLM inference pipelines and AI service operations.
</li></ul>3. Programming &amp; Software Design
<ul><li>Strong programming skills in Python with experience building and supporting production systems.
</li><li>Experience with scripting and automation using Python and Bash.
</li><li>Familiarity with configuration management and orchestration tools.
</li></ul>4. Systems &amp; Infrastructure
<ul><li>Strong Linux fundamentals include shell, containers, system services, and networking basics (DNS, TLS, HTTP/gRPC).
</li><li>Experience working with cluster schedulers such as Slurm or equivalent systems.
</li><li>Experience operating distributed systems with high availability and fault tolerance.
</li></ul>5. Observability &amp; Monitoring
<ul><li>Hands‑on experience with monitoring and logging tools such as Prometheus, Grafana, ELK, or Loki.
</li><li>Understanding of incident management, service health metrics, and system reliability monitoring.
</li></ul>6. DevOps &amp; SRE Practices
<ul><li>Solid understanding of SDLC, release processes, and operational reliability practices.
</li><li>Familiarity with CI/CD pipelines and Infrastructure‑as‑Code tools.
</li></ul><div></div>Preferred Skillset
<ul><li>Experience with GenAI, Agentic AI systems, or LLM orchestration frameworks.
</li><li>Exposure to LangChain, AutoGen, or RAG‑based systems.
</li><li>Experience with additional ML frameworks such as TensorFlow, JAX, or Ray.
</li><li>Knowledge of GPU/accelerator‑based systems and high‑performance networking (RDMA, InfiniBand, RoCE).
</li><li>Experience with advanced MLOps workflows or large‑scale AI platform operations.
</li></ul><div></div>Qualifications
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in engineering, Computer Science, AI/ML, or a related field.
</li><li>2&ndash;8 years of software, systems, or infrastructure engineering experience, preferably in production or datacenter environments.
</li></ul>What's on Offer
Apart from working with great people, we offer the below:
<ul><li>Salary including housing &amp; transport allowance
</li><li>Stock (RSU's) and performance related bonus
</li><li>16 weeks fully paid Maternity Leave
</li><li>6 weeks fully paid Paternity Leave
</li><li>Employee stock purchase scheme
</li><li>Child Education Allowance
</li><li>Relocation and immigration support (if needed)
</li><li>Life and Medical Insurance
</li><li>Live+ Well Reimbursement for health and recreational membership fees
</li></ul>Minimum Qualifications:
<ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
 
 
<ul><li>2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
</li></ul>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
<div>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</div>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers .</div>

Infrastructure & Site Reliability Engineer – Datacentre AI Engineering - Riyadh, KSA

<div>Job Description:
The charge of creating and developing intelligent solutions using Artificial Intelligence technologies with a focus on generative AI and data science.
The role entails converting data into useful insights and developing AI powered applications that improve decision making and enhance operational efficiency.
Tools &amp; Technologies: Dataiku, Sql server, Power bi, and aws bedrock
Key Responsibilities:<ul><li>
Design, develop, train, and optimize machine learning models for real applications or use cases.</li><li>
Translate business and product requirements into scalable ML/AI solutions.</li><li>
Implement feature engineering, model selection, tuning, and evaluation techniques.</li></ul><ul><li>
Develop, and deploy ML models into production environments with high availability and performance.</li><li>
Build and maintain ML pipelines (training, validation, deployment, monitoring).</li><li>
Monitor model performance, data drift, and model decay; retrain models as needed.</li><li>
Ensure models meet reliability, scalability, and security standards.</li><li>
Work closely with Data Scientists, Product Managers, and Software Engineers.</li><li>
Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.</li><li>
Participate in design and code reviews, ensuring engineering best practices.</li><li>
Optimize models for latency, throughput, and cost.</li><li>
Implement experimentation frameworks (A/B testing, offline evaluation).</li><li>
Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul> 
Requirements 
Requirements &amp; Qualifications:<ul><li>
+4 years of hands-on experience in Machine Learning or applied AI roles.</li><li>
Strong programming skills in Python (and/or Java, Scala).</li><li>
Solid understanding of ML algorithms (supervised, unsupervised, deep learning).</li><li>
Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.</li><li>
Experience deploying models using Docker, Kubernetes, or cloud ML services.</li><li>
Strong knowledge of data structures, algorithms, and software engineering principles.</li><li>
Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.</li><li>
Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).</li><li>
Experience with big data technologies (Spark, Kafka, Databricks).</li><li>
Background in NLP, Computer Vision, or Generative AI.</li><li>
Strong problem-solving and analytical thinking</li><li>
Production-first mindset</li><li>
Data-driven decision making</li><li>
High Collaboration and communication skills</li></ul></div>

AI developer

Gathern

<div>JOB PURPOSE: 
Lead the design, development, and scaling of advanced machine learning systems that power Gathern&rsquo;s marketplace intelligence across discovery, pricing, personalization, and trust domains. The role combines deep technical expertise with strategic thinking to translate complex data into production-grade predictive and decisioning systems. Focuses on architecting scalable ML infrastructure, ensuring model robustness and reliability, and driving measurable business impact through experimentation, optimization, and cross-functional leadership 
 
KEY ACCOUNTABILITIES:<ul><li>
Architect ML systems / end-to-end pipelines / scalable and production-ready solutions</li><li>
Lead model development/pricing and ranking algorithms / improved conversion and revenue yield</li><li>
Design forecasting solutions/demand and supply models / optimized inventory and occupancy planning</li><li>
Enhance risk models/fraud detection systems / reduce cancellations and policy violations</li><li>
Establish MLOps standards/deployment and monitoring frameworks / reliable and maintainable model operations</li><li>
Drive experimentation / A/B testing and validation frameworks / data-driven product improvements</li><li>
Collaborate cross-functionally / product, engineering, and data teams / aligned metrics and business impact</li><li>
Define data strategy/feature engineering and data sourcing / improved model performance and coverage</li><li>
Ensure model governance/data quality and integrity / trusted and compliant ML systems</li><li>
Mentor team members / technical guidance and best practices / elevated team capability and output quality</li><li>
Optimize model performance/tuning and retraining strategies / sustained accuracy and efficiency</li><li>
Evaluate new approaches/algorithms and technologies / continuous innovation and competitive advantage</li><li>
Communicate insights/model performance and impact / informed stakeholder decision-making.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field</li></ul><ul><li>
5&ndash;8+ years of experience in applied machine learning, data science, or ML engineering roles</li><li>
Proven experience designing, deploying, and scaling ML systems in production environments</li><li>
Strong experience with large-scale data processing and distributed systems (e.g., Spark, Beam)</li><li>
Advanced proficiency in Python and ML frameworks such as TensorFlow or PyTorch</li><li>
Deep understanding of MLOps practices (CI/CD, model lifecycle management, feature stores, monitoring)</li><li>
Strong expertise in SQL and data engineering tools (Airflow, Kafka, DBT, etc.)</li><li>
Experience with experimentation frameworks and causal inference methods is a plus</li><li>
Strong system design and architecture skills for ML-driven products</li><li>
Excellent problem-solving skills with a strong analytical and business-oriented mindset</li><li>
Ability to lead initiatives, influence stakeholders, and mentor junior team members</li></ul></div>

Senior Machine Learning Engineer

CNTXT

<div>
 
 
 Job Summary
 
 
 
 We are seeking a highly skilled Data Scientist to lead the design, development, and deployment of advanced autonomous agents and Large Language Models (LLMs). This role offers the chance to drive innovative AI solutions in a collaborative, dynamic environment, working on cutting-edge systems that solve real-world challenges.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Agent Development: Design and implement autonomous agents that perform tasks, call external tools/APIs, and generate code to solve complex problems.
 </li>
 <li>
 LLM Integration: Develop and integrate Large Language Models to enhance agent capabilities in decision-making and natural language processing.
 </li>
 <li>
 Tooling: Equip agents with the right toolchains&mdash;RAG, vector DBs, third-party APIs&mdash;to streamline task execution.
 </li>
 <li>
 Safety &amp; Ethics: Incorporate guardrails, alignment tests, and compliance standards to ensure secure, reliable operation.
 </li>
 <li>
 Performance Optimisation: Use MLOps/DevOps best practices to monitor, benchmark, and refine models for cost-efficient scale.
 </li>
 <li>
 Collaboration: Partner with cross-functional teams to align technical solutions with business goals.
 </li>
 <li>
 Performance Optimization: Refine agent and LLM performance using MLOps and DevOps best practices.
 </li>
 <li>
 Deployment: Own end-to-end rollout on cloud (AWS, Azure, or GCP), containerising with Docker/Kubernetes where appropriate.
 </li>
 <li>
 Cross-functional Alignment: Work closely with product, engineering, and domain SMEs to translate business goals into technical roadmaps.
 </li>
 <li>
 Mentorship: Coach and review work of junior data scientists/ML engineers.
 </li>
 <li>
 Innovation: Dedicate a portion of your time to tracking AI trends and prototyping new autonomous-agent capabilities.
 </li>
 <li>
 Communication: Present insights and outcomes clearly to both technical and non-technical stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Master&rsquo;s or Ph.D. in Computer Science, Artificial Intelligence, or related field (or equivalent practical experience).
 </li>
 <li>
 5 + years in data science/ML engineering, with 2 + years building AI systems that include autonomous agents or LLMs.
 </li>
 <li>
 Proven record of deploying agentic systems with integrated safety features.
 </li>
 <li>
 Expert-level Python and deep familiarity with PyTorch or TensorFlow.
 </li>
 <li>
 Hands-on experience running production workloads on at least one major cloud platform.
 </li>
 <li>
 Solid grasp of MLOps (CI/CD, model monitoring, IaC).
 </li>
 <li>
 Strong problem-solving ability and clear, concise communication skills.
 </li>
 </ul>
</div>

Data Scientist

<div><div>We help the world run better 
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div><div></div> 
What you&rsquo;ll build 
In this role, you'll build and operationalize machine learning and AI capabilities that from idea to production and deliver measurable product value. You'll develop data move pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for use cases such as recommendation, forecasting, anomaly detection, classification, NLP, semantic search, and generative AI.
Your work will include feature engineering, experiment design, model tuning, offline and online validation, and integration of models into scalable product architectures. You'll help improve LLM-based workflows, including prompt design, retrieval-augmented generation, vector search, guardrails, and response quality evaluation. You&rsquo;ll also strengthen the engineering backbone around AI through CI/CD, monitoring, observability, testing, and model lifecycle automation so solutions are reliable, cost-aware, secure, and ready for enterprise scale. 
What you bring: 
<ul><li>
You bring strong programming skills in Python, along with working knowledge of Java or Go, for building production-grade services and APIs
</li><li>You have a solid understanding of machine learning fundamentals, including supervised and unsupervised methods such as classification, regression, clustering, ranking, and recommendation systems
</li><li>You have hands-on experience with deep learning frameworks (e.g., PyTorch or TensorFlow) for model training, fine-tuning, and inference
</li><li>You demonstrate strong capabilities in data preparation, feature engineering, data validation, and model evaluation using appropriate offline and online metrics
</li><li>You have experience building, deploying, and integrating ML models into production systems through batch, real-time, or streaming pipelines
</li><li>You are familiar with generative AI concepts, including LLMs, embeddings, vector databases, prompt engineering, and retrieval-augmented generation, and how to apply them in practical use cases
</li><li>You bring working knowledge of MLOps and modern data infrastructure, including experiment tracking, model versioning, CI/CD, and tools such as Spark, Kafka, Airflow, and feature stores
</li><li>You have experience operating ML systems in production, including monitoring for drift, latency, accuracy, cost, bias, and performing debugging and failure analysis to ensure reliability and business impact</li></ul> 
About You 
<ul><li>
You have 1-3+ years of experience in machine learning engineering, software engineering, or a related field, with a track record of deploying models into production
</li><li>You are passionate about building reliable, scalable ML systems and take ownership of delivering end-to-end solutions
</li><li>You balance experimentation with engineering rigor, making thoughtful trade-offs to ensure models are both innovative and production-ready
</li><li>You are a collaborative problem-solver who thrives in ambiguous environments and is motivated by delivering measurable business impact</li></ul> 
Where you belong:<div> 
You will be part of a growing team of AI and industry experts dedicated to serving customers across the Kingdom of Saudi Arabia / United Arab Emirates. We are building a collaborative, high‑impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets.</div><div>
This team thrives on working together to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real‑world impact matters. This is a place for people who enjoy building something new. You will thrive here if you are customer‑centric, motivated by meaningful outcomes, and comfortable navigating ambiguity in a fast‑evolving AI landscape.</div> 
About the team
We are a team of engineers passionate about building valuable, scalable AI frameworks that drive real business impact. We thrive on solving challenging problems, innovating with cutting-edge technologies, and collaborating closely to deliver AI systems that are reliable, high-performing, and ready for production. Our team values ownership, technical excellence, and creating solutions that stand the test of scale and complexity.<div> 
Bring out your best 
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
 
 
We win with inclusion 
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world. 
 
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com. 
 
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. 
 
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements. 
 
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div> 
AI Usage in the Recruitment Process</div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div>Please note that any violation of these guidelines may result in disqualification from the hiring process. 
 
Requisition ID: 450210 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

Machine Learning Engineer

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