senior machine learning engineer

Siemens

<div>
 <strong>
  About Brightly
  <br/>
  <br/>
 </strong>
 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.
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 <br/>
 <strong>
  The Opportunity
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  <br/>
 </strong>
 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.
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 <strong>
  What You&rsquo;ll Do
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 </strong>
 <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.
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   <br/>
  </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
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 <ul>
  <li>
   Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
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   <br/>
  </li>
 </ul>
 <strong>
  What You&rsquo;ll Bring
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  <br/>
 </strong>
 <strong>
  Required experience
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  <br/>
 </strong>
 <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.
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   <br/>
  </li>
 </ul>
 <strong>
  Nice to have
  <br/>
  <br/>
 </strong>
 <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.)
   <br/>
   <br/>
  </li>
 </ul>
 How you&rsquo;ll work
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 <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.)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
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  <br/>
 </strong>
 <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.)
   <br/>
   <br/>
  </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.
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 <strong>
  The Brightly culture
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  <br/>
 </strong>
 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>


Senior Machine Learning Engineer

Gathern

<div><p><b>JOB PURPOSE:</b><br>
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<br>
<br>
<b>KEY ACCOUNTABILITIES:</b></p><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><br>
<b>
Requirements</b><br>
<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>

Arrow Electronics

<div>
 <strong>
  Position
  <br/>
  <br/>
 </strong>
 Data Scientist / Senior Machine Learning Engineer
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  Position Overview:
  <br/>
  <br/>
 </strong>
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
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 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
  </li>
  <li>
   Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
  </li>
  <li>
   Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
  </li>
  <li>
   Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
  </li>
  <li>
   Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
  </li>
  <li>
   Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
  </li>
  <li>
   Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
  </li>
  <li>
   Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
  </li>
  <li>
   Strong knowledge of machine learning frameworks and libraries.
  </li>
  <li>
   Expertise in data preprocessing, feature engineering, and model selection.
  </li>
  <li>
   Familiarity with large language models and AI agent design.
  </li>
  <li>
   Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
  </li>
  <li>
   Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
  </li>
  <li>
   Experience with vectorized databases and unstructured search engines is a plus.
  </li>
  <li>
   A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
  </li>
  <li>
   Publications or contributions to open-source projects are a plus.
   <br/>
   <br/>
  </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 <br/>
 <br/>
 <strong>
  Location:
  <br/>
  <br/>
 </strong>
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
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 <br/>
 <strong>
  Time Type
  <br/>
  <br/>
 </strong>
 Full time
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 <strong>
  Job Category
  <br/>
  <br/>
 </strong>
 Information Technology
</div>


Data Scientist / Senior Machine Learning Engineer

Enigma

<div><h3 class="jobSectionHeader"><b>The Opportunity</b></h3>
<p>
This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it.</p>
<p>
We are looking for an experienced Senior Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma's customer-facing data products.</p>
<p>
In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery.</p>
<h3 class="jobSectionHeader"><b>
The Role</b></h3>
<p>
At the core of Enigma's product is our data, which makes both data science and delivery systems central to what we build.</p>
<p>
As a Senior ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You'll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems.</p>
<p>
This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems.</p>
<h3 class="jobSectionHeader"><b>
What You'll Do</b></h3>
<ul><li>Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems</li>
<li>Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS</li>
<li>Evaluate and evolve our search technology stack, driving technical design decisions across indexing strategies, retrieval architecture, and system performance tradeoffs</li>
<li>Lead end-to-end work from research design through experimentation, productionization, and customer-facing delivery</li>
<li>Design evaluation frameworks for measuring relevance, precision/recall, ranking quality, and user engagement signals</li>
<li>Improve query understanding via techniques like embedding models, vector search, hybrid retrieval, and query rewriting</li>
<li>Detect and investigate anomalies in search performance, ranking behavior, and data freshness, tracing issues to root cause</li>
<li>Partner closely with Product, Engineering, and client stakeholders to improve search experience and discoverability</li>
<li>Mentor teammates and help raise the bar for experimentation rigor, system design, and operational excellence</li>
</ul><h3 class="jobSectionHeader"><b>What Makes This Role Exciting?</b></h3>
<ul><li><b>Impact: </b>At Enigma, data science and machine learning aren't just used to make product decisions; they are the product. Your work will directly shape how customers find, explore, and trust our data.</li>
<li><b>Technical Challenge</b>: This role spans some of the hardest challenges in search relevance, large-scale retrieval systems, ranking models, APIs, and distributed systems. If you like a technical challenge, this role is for you.</li>
<li><b>Ownership</b>: You'll have meaningful autonomy to shape both research direction and the production systems that power it, including having a strong voice in our tooling and vendor ecosystem.</li>
<li><b>Customer Proximity: </b>Your work will directly influence how sophisticated customers integrate Enigma data into critical workflows and decision-making systems.</li>
</ul><h3 class="jobSectionHeader"><b>Our Ideal Candidate</b></h3>
<ul><li>Brings 5+ years of experience across machine learning, software engineering, data science, or data-intensive product systems</li>
<li>Has strong programming proficiency in Python and experience operating within cloud environments (AWS preferred)</li>
<li>Demonstrated applied, production-level expertise in <b>two or more</b> of the following technical domains: information retrieval, ranking systems, NLP/embedding models, or distributed systems.</li>
<li>Has experience designing, fine-tuning, and operating high-scale backend systems, APIs, or data delivery platforms</li>
<li>Brings strong judgment in ambiguous environments where relevance signals and ground truth are noisy or implicit</li>
<li>Effectively communicates technical concepts and tradeoffs to technical and non-technical audiences</li>
<li>Thrives in highly collaborative environments with strong ownership and fast iteration cycles</li>
<li>Has an advanced degree in a quantitative discipline or equivalent deep industry experience</li>
</ul><h3 class="jobSectionHeader"><b>Bonus Points If You</b></h3>
<ul><li>Have deep experience with our core stack (Typesense, Python, AWS) or similar retrieval infrastructure (Elasticsearch, OpenSearch, FAISS)</li>
<li>Have built customer-facing search or recommendation systems or APIs</li>
<li>Have worked on query understanding, embeddings, LLM-powered retrieval, or hybrid search systems</li>
<li>Have mentored senior engineers or data scientists and raised the technical bar across disciplines</li>
</ul><h3 class="jobSectionHeader"><b>About Us</b></h3>
<p>
At Enigma, we're building the single, most reliable source of data on businesses to power the future of financial services. By engineering better data from hundreds of public and third-party sources, we aim to tell the complete story of every business, so that companies of every size can access the financial services they need to grow and thrive. Our core values &ndash; generosity, curiosity, ingenuity, &amp; drive &ndash; guide everything we do, from how we make our most important product decisions to how we work with and support one another on a daily basis. We're a team of curious, driven individuals with diverse backgrounds and skills, but we're all passionate about engineering deeper understanding through data&mdash;together. If this resonates, we would love to hear from you!</p>
<p>
We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.</p>
<p><i>
Salary Range: $160,000-$210,000</i></p>
<p><i>
A note on salary ranges: we pride ourselves on paying competitively for our size and industry. Salary is one piece of a total Enigma compensation package that includes additional benefits and opportunities. All of our compensation packages include equity because we believe 100% of Enigma employees should have the option to purchase ownership in the company and benefit from the value we're creating together.</i></p></div>

Senior Machine Learning Engineer, Match Team

Match Group

<div><div><b>Hinge is the dating app designed to be deleted</b></div><div></div><div><br>
In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we&rsquo;re on a mission to inspire intimate connection to create a less lonely world. We&rsquo;re obsessed with understanding our users&rsquo; behaviors to help them find love, and our success is defined by one simple metric&ndash; setting up great dates. With millions of users across the globe, we&rsquo;ve become the most trusted way to find a relationship, for all.</div><div></div><div><b><br>
About the Role</b></div>
<div></div>
<div>Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust &amp; Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection.</div>
<h3 class="jobSectionHeader"><b>Responsibilities</b></h3><ul>
<li>Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety.</li>
<li>Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines.</li>
<li>Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions.</li>
<li>Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations.</li>
<li>Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety.</li>
<li>Stay abreast of new trends and research in AI/ML that can be applied to Trust &amp; Safety initiatives to improve detection, user safety, and stay ahead of potential threats.</li>
</ul><h3 class="jobSectionHeader"><b>What We're Looking For</b></h3><ul>
<li><b>Strong programming skills:</b> Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines</li>
<li><b>Domain expertise:</b> Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus .</li>
<li><b>System design &amp; architecture:</b> Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference.</li>
<li><b>Evaluation frameworks for LLMs:</b> Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features.</li>
<li><b>Cloud and data platform proficiency: </b>The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus.</li>
<li><b>Data engineering knowledge: </b>Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow.</li>
<li><b>Strategic technical leadership skills: </b>Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives.</li>
<li><b>Collaboration and communication skills:</b> The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.</li>
<li><b>Strong written communication: </b>The ability to communicate complex ideas and technical knowledge through documentation.</li>
</ul><div><b>Prior Experience</b></div>
<ul><li>4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust &amp; Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred.</li>
<li>2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting</li>
<li>1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies.</li>
<li>1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc.</li>
<li>A degree in computer science, engineering, or a related field (or equivalent practical experience).</li>
</ul><div>Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.</div><div><b>
As a member of our team, you&rsquo;ll enjoy:</b></div><div></div><div><b><br>
401(k) Matching:</b> We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.</div><div></div><div><b><br>
Professional Growth: </b>Get an annual Learning &amp; Development stipend once you&rsquo;ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day.</div><div></div><div><b><br>
Parental Leave &amp; Planning:</b> When you become a new parent, you&rsquo;re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.)</div><div></div><div><b><br>
Fertility Support:</b> You&rsquo;ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible.</div><div></div><div><b><br>
Date Stipend:</b> All Hinge employees receive a $100 monthly stipend for epic dates&ndash; Romantic or otherwise. Hinge Premium is also free for employees and their loved ones.</div><div></div><div><b><br>
ERGs:</b> We have eight Employee Resource Groups (ERGs)&mdash;Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents &mdash;that hold regular meetings, host events, and provide dedicated support to the organization &amp; its community.</div><div></div><div><b><br>
At Hinge, our core values are&hellip;</b></div><div></div><div><b><br>
Authenticity:</b> We share, never hide, our words, actions and intentions.</div><div></div><div><b><br>
Courage:</b> We embrace lofty goals and tough challenges.</div><div></div><div><b><br>
Empathy:</b> We deeply consider the perspective of others.</div><div></div><div><b><br>
Diversity inspires innovation</b></div><div></div><div><br>
Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.</div><div></div><div><b><i><br>
If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know.<br>
</i></b></div><div></div><br>
<div><i>#Hinge</i></div>
<p>
.</p></div>

Senior Machine Learning Engineer, Trust & Safety

Waymo

<div><p>MOUNTAIN VIEW, CALIFORNIA, UNITED STATES</p>
<p>FULL-TIME</p>
<p>SOFTWARE ENGINEERING</p>
<p>4330</p></div>
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</div><div><div><p>Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver&mdash;The World's Most Experienced Driver&trade;&mdash;to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo&rsquo;s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.</p></div><p>
The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar).</p>
<p>
To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver.</p>
<p>
In this role, you will report to a Senior Staff Engineering Manager.</p>
<p><b>
You will:</b></p>
<ul>
<li>Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo.</li>
<li>Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization.</li>
<li>Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments.</li>
<li>Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products.</li>
<li>Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions.</li>
<li>Mentor and provide technical guidance to other engineers on the team.</li>
</ul>
<p><b>You have:</b></p>
<ul>
<li>MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.</li>
<li>5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record.</li>
<li>Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications.</li>
<li>Deep expertise in 3D World Modeling or 3D computer vision.</li>
<li>Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting).</li>
<li>Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow.</li>
</ul>
<p><b>We prefer:</b></p>
<ul>
<li>PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation..</li>
<li>Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes.</li>
<li>Experience with autonomous systems, robotics, or autonomous vehicle simulation.</li>
<li>Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving.</li>
<li>Experience in C++ for production systems.</li></ul><br>
<p></p>
<p>
#LI-Hybrid</p><div><div>
<div>
<p>The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.</p>
<p>
Waymo employees are also eligible to participate in Waymo&rsquo;s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.</p>
</div>
<div>Salary Range</div>
<div>$204,000&mdash;$259,000 USD</div></div></div></div></div></div></div>

<div><div><b>We help the world run better</b><br>
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><p><b><br>
What you&rsquo;ll build</b></p><p>
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.
</p><p>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.</p><p></p><p><b><br>
What you bring:</b></p><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><p></p><p><b><br>
About You</b></p><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><p></p><p><b><br>
Where you belong:</b></p><p>
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.</p><p>
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.</p><p></p><p><b><br>
About the team</b></p><p>
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.</p><p></p><div><b><br>
Bring out your best</b><br>
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.
<br>
<br>
<b>We win with inclusion</b><br>
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.<br>
<br>
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.<br>
<br>
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.<br>
<br>
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.<br>
<br>
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div><b><br>
AI Usage in the Recruitment Process</b></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><p>Please note that any violation of these guidelines may result in disqualification from the hiring process.<br>
<br>
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</p></div>

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