senior machine learning engineer

Unifonic

<div>
 
 Job Description
 
 
 
 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.
 
 
 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!
 
 
 
 Meet the team!
 
 
 
 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.
 
 
 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.
 
 
 
 Help Us Shape The Future Of Communication By
 
 
 
 <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.
 
 
 </li>
 </ul>
 
 Job Requirements
 
 
 
 
 What you'll bring:
 
 
 
 <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:
 
 
 </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 
 
 Large Language Models (LLMs) and their fine-tuning/adaptation
 
 
 Vector embeddings and similarity search
 
 
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 
 
 <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.
 
 
 </li>
 </ul>
 
 As a Unifone you will receive a range of benefits:
 
 
 
 <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>

Senior Machine Learning Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

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>

Sana Commerce

<div>
 
 
 Company Description
 
 
 
 What started in 2007 with a pizza and a plan has grown into a fast-moving SaaS company empowering manufacturers, distributors, and wholesalers to thrive in complex B2B commerce.
 
 
 Our mission is simple: help businesses build stronger relationships through seamless digital commerce.
 
 
 At Sana Commerce, we're looking for a Sr.
 
 Data Engineer (ML/AI)
 
 to design, build, and scale data systems that power our analytics and machine learning initiatives. Your work will ensure high-quality, reliable, and ML-ready data pipelines that enable both traditional analytics and advanced AI-driven solutions across the business.
 
 
 
 
 
 
 Job Description
 
 
 
 
 What you'll be doing
 
 
 <ul>
 <li>
 Designing and maintaining
 
 data pipelines optimized for ML/AI workloads
 
 , including handling of large-scale, unstructured, and semi-structured data.
 </li>
 <li>
 Building
 
 feature pipelines and feature stores
 
 that ensure reusability and consistency of data used by machine learning models.
 </li>
 <li>
 Collaborating with Data Scientists and ML Engineers to understand
 
 data requirements for training, validation, and production deployment
 
 .
 </li>
 <li>
 Ensuring
 
 data quality, lineage, and governance
 
 meet standards required for AI/ML applications.
 </li>
 <li>
 Supporting
 
 MLOps practices
 
 by integrating data pipelines with model training, monitoring, and deployment workflows.
 </li>
 <li>
 Leveraging distributed processing frameworks (e.g., Spark, Databricks, Azure Synapse) for
 
 scalable ML data processing
 
 .
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 What you bring
 
 
 <ul>
 <li>
 
 8+ years
 
 of experience as a Data Engineer, working with Azure and Databricks, ideally with exposure to
 
 ML/AI-related data workflows
 
 .
 </li>
 <li>
 College degree that demonstrates your analytical abilities, such as Econometrics, Computer Sciences, Mathematics or similar;
 </li>
 <li>
 Excellent analytical and problem-solving skills;
 </li>
 <li>
 Experience with
 
 data preparation for ML/AI
 
 : managing large datasets, feature engineering, and real-time or batch data pipelines.
 </li>
 <li>
 Familiarity with
 
 MLOps concepts
 
 and how data engineering supports model lifecycle management.
 </li>
 <li>
 Experience with orchestration frameworks (Airflow, Prefect, or Azure Data Factory) for
 
 complex ML pipelines
 
 .
 </li>
 <li>
 Knowledge of unstructured data processing (text, images, logs) is a plus.
 </li>
 <li>
 Strong SQL and Python skills; experience with distributed data processing (PySpark, Dask, etc.) is a plus.
 </li>
 </ul>
 
 
 
 
 
 Why you&rsquo;ll love working here
 
 
 <ul>
 <li>
 Impact from day one &ndash; Join a scale-up where your ideas shape how global businesses operate online.
 </li>
 <li>
 Continuous learning &ndash; Access a structured onboarding rated 9.1/10 by previous hires, mentorship, and feedback culture.
 </li>
 <li>
 Hybrid flexibility &ndash; Work from our office 3 days per week and from home 2 days.
 </li>
 <li>
 Career growth &ndash; Expand your technical and leadership scope in a company built for long-term success.
 </li>
 </ul>
 
 
 Our values
 
 
 
 At Sana Commerce, our values drive everything we do:
 
 <ul>
 <li>
 Champions of Our League &ndash;
 
 We deliver lasting success, balancing quick wins and long-term value
 
 </li>
 <li>
 Supercharge Our Customers &ndash;
 
 We&rsquo;re revolutionizing B2B commerce together, helping our customers to lead and succeed.
 
 </li>
 <li>
 Determined to Grow &ndash;
 
 We embrace challenges, growing and raising the bar for ourselves and our industry.
 
 </li>
 <li>
 Bold Together &ndash;
 
 We dare to be bold because we have each other&rsquo;s back.
 
 </li>
 </ul>
 
 
 
 
 
 Ready to build reliability that scales?
 
 
 
 Apply now and help shape the foundation of our next-generation SaaS platform.
 
</div>

<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 lead the design and delivery of production-grade ML and generative AI systems that solve complex product and business problems at scale. You'll own architecture and implementation across data pipelines, feature stores, training workflows, model-serving infrastructure, online experimentation, and observability.
You'll drive advanced use cases across deep learning, NLP, ranking, recommendation, forecasting, semantic retrieval, and LLM applications, including RAG, tool use, evaluation harnesses, and safety controls. Your work will directly shape performance, reliability, latency, and cost efficiency in live environments. You&rsquo;ll guide technical direction on topics such as model selection, distributed training and inference, GPU utilization, model compression, prompt and retrieval optimization, drift detection, retraining strategy, and responsible AI controls. You&rsquo;ll mentor other engineers and turn best practices into reusable patterns and platform capabilities. 
What you bring:<ul><li>
You bring expert-level programming skills in Python, along with strong software engineering expertise in languages such as Java or Go, enabling you to build scalable, production-grade systems
</li><li>You have deep knowledge of machine learning, deep learning, and optimization techniques across structured data, NLP, search, ranking, and recommendation problems
</li><li>You have extensive experience designing and operating end-to-end ML systems, from data ingestion and experimentation to deployment, observability, and lifecycle management
</li><li>You bring strong hands-on experience with modern ML and LLM tooling (e.g., PyTorch, TensorFlow, scikit-learn), including fine-tuning, evaluation, orchestration, and model serving
</li><li>You have practical experience building generative AI applications using embeddings, vector databases, RAG pipelines, agent workflows, prompt engineering, and guardrails
</li><li>You bring deep expertise in MLOps and platform engineering, including model registries, feature stores, CI/CD, infrastructure as code, experiment tracking, and automated validation
</li><li>You have a strong architectural understanding of distributed systems, event-driven services, streaming data, and cloud-native ML platforms, with the ability to optimize for performance, scalability, reliability, and cost
</li><li>You define robust evaluation and governance strategies, including offline benchmarking, online experimentation, hallucination analysis, model risk assessment, and responsible AI practices</li></ul> 
About You<ul><li>
You bring 7-9+ years of experience in software engineering and machine learning, with a track record of leading and delivering complex, production-scale AI systems</li><li>
You combine strong product judgment with technical depth, translating ambiguous business problems into scalable, high-impact AI solutions
</li><li>You thrive in complex, fast-moving environments and bring clarity, ownership, and strategic thinking to drive long-term platform success</li></ul> 
Where you belong:
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.
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. 
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.
#LI-LP1<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: 450236 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

<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> 
What you&rsquo;ll build 
In this role, you'll lead the design and delivery of production-grade ML and generative AI systems that solve complex product and business problems at scale. You'll own architecture and implementation across data pipelines, feature stores, training workflows, model-serving infrastructure, online experimentation, and observability.
You'll drive advanced use cases across deep learning, NLP, ranking, recommendation, forecasting, semantic retrieval, and LLM applications, including RAG, tool use, evaluation harnesses, and safety controls. Your work will directly shape performance, reliability, latency, and cost efficiency in live environments. You&rsquo;ll guide technical direction on topics such as model selection, distributed training and inference, GPU utilization, model compression, prompt and retrieval optimization, drift detection, retraining strategy, and responsible AI controls. You&rsquo;ll mentor other engineers and turn best practices into reusable patterns and platform capabilities. 
What you bring: 
<ul><li>
You bring expert-level programming skills in Python, along with strong software engineering expertise in languages such as Java or Go, enabling you to build scalable, production-grade systems</li><li>
You have deep knowledge of machine learning, deep learning, and optimization techniques across structured data, NLP, search, ranking, and recommendation problems</li><li>
You have extensive experience designing and operating end-to-end ML systems, from data ingestion and experimentation to deployment, observability, and lifecycle management</li><li>
You bring strong hands-on experience with modern ML and LLM tooling (e.g., PyTorch, TensorFlow, scikit-learn), including fine-tuning, evaluation, orchestration, and model serving</li><li>
You have practical experience building generative AI applications using embeddings, vector databases, RAG pipelines, agent workflows, prompt engineering, and guardrails</li><li>
You bring deep expertise in MLOps and platform engineering, including model registries, feature stores, CI/CD, infrastructure as code, experiment tracking, and automated validation</li><li>
You have a strong architectural understanding of distributed systems, event-driven services, streaming data, and cloud-native ML platforms, with the ability to optimize for performance, scalability, reliability, and cost</li><li>
You define robust evaluation and governance strategies, including offline benchmarking, online experimentation, hallucination analysis, model risk assessment, and responsible AI practices</li></ul> 
About You<ul><li>
You bring 7-9+ years of experience in software engineering and machine learning, with a track record of leading and delivering complex, production-scale AI systems</li><li>
You combine strong product judgment with technical depth, translating ambiguous business problems into scalable, high-impact AI solutions</li><li>
You thrive in complex, fast-moving environments and bring clarity, ownership, and strategic thinking to drive long-term platform success</li></ul> 
Where you belong: 
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.
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. 
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: 450218 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

Apple

Would you like to play a part in building the next generation of generative AI applications at Apple? We&rsquo;re looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple&rsquo;s Generative-AI powered features and products. In this role you&rsquo;ll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple&rsquo;s Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. 
 
Description 
 
This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology &amp; infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. 
 
Producing safety evaluations that uphold Apple&rsquo;s Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience. 
 
This role heavily draws on applied data science, scientific investigation and interpretation, cross-functional communication and collaboration, and metrics reporting and presentation.&quot;,&quot;responsibilities&quot;:&quot;Develop metrics for evaluation of safety and fairness risks inherent to generative AI features. 
 
Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods. 
 
Develop auto-grading technologies and approaches for application in safety evaluations of generative AI features. 
 
Provide technical direction and expertise to team-wide initiatives in safety auto-grading. 
 
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations. 
 
Work with highly-sensitive content with exposure to offensive and controversial content. 
 
Preferred Qualifications 
 
Experience working in the Responsible AI space. 
 
Prior scientific research and publication experience. 
 
Strong organizational and operational skills working with large, multi-functional, and diverse teams. 
 
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable. 
 
Minimum Qualifications 
 
MS, or PhD in Computer Science, Machine Learning, Statistics, or related fields; or an equivalent qualification acquired through other avenues. 
 
Experience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures. 
 
Strong engineering skills and experience in writing production-quality code in Python. 
 
Deep experience in foundation model-based AI programming (i.e.: using DSPy for optimizing foundation model prompts, for example) and a drive to innovate in this space. 
 
Experience working with noisy, crowd-based data labels and human evaluations. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety

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AIML - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety