software engineer

software engineer, ai product Jobs in San Francisco

software engineer, ai product

staff machine learning engineer Jobs in San Francisco

staff machine learning engineer

2026 applied science internship - united states, phd student science recruiting, frontier ai & robotics Jobs in San Francisco

2026 applied science internship - united states, phd student science recruiting, frontier ai & robotics

2026 phd software engineer intern (machine learning), united states Jobs in San Francisco

2026 phd software engineer intern (machine learning), united states

2026 phd software engineer intern machine learning united states

Uber

<div>We're looking for PhD candidates in the machine learning and optimization domain to intern with a variety of teams during summer 2026 (12 weeks). You will be embedded in an engineering team and work closely with other specialists, data scientists, and product managers. As a PhD intern, you will work on an exciting yet bold problem independently, under the supervision of an experienced engineer on that team.
 
 
About the Role
 
 
At Uber, we work on many ambitious engineering products covering many lines of business as well as the underlying platform technologies that power those businesses. We foster growth and increase profitability of Uber by pushing the frontiers of machine learning, constrained optimization, statistics, data science and economics and developing highly reliable and scalable platforms to accelerate Uber's impact on the transportation industry.
 
 
As a PhD software engineer intern, you will have a lot of opportunities to work with product managers, data scientists and, of course, engineers from different teams. You will have an opportunity to learn how to iterate over a product for greater success while demonstrating your area of expertise (machine learning, statistics, constrained optimization, distributed system, etc.). This is a unique opportunity to grow your skills with real-world experience and do highly impactful, yet fun work at the same time. It is an ambitious yet rewarding job!
 
 
Team Options
<ul><li>The Delivery Marketplace: Consumer and Courier Pricing, Matching and Logistics is responsible for building the core technology across the delivery line of business including food delivery, grocery, and retail last mile. These include a diverse set of transformational projects and impactful products ranging from finding the optimal match between jobs and earners in the delivery space, to setting optimal prices for Eaters and Couriers. The organization is formed of talented teams of engineers and scientists working side by side on the state of the art innovations on the matching objective function, pricing algorithms, and promotions. To achieve these goals, we leverage big data tools and apply advanced machine learning models to drive top line and bottom line business outcomes.
</li><li>The Trusted Identity org inspires trust in the Uber business cycle through verified and authentic identities. The Account Integrity team prevents fake identities from operating on the platform, and ensures that accounts are not duplicated nor fraudulent to enhance accountability. The Identity Verification team ensures accounts are created by real humans by verifying their attributes. The Account Security team is responsible for defending account holders from fraud related to phishing and ATO (account takeover) attempts. The Device Intelligence team is responsible for collecting device signals that are critical for the other teams to reliably achieve their goals.
</li><li>The Uber Risk engineering team is tackling challenges related to fraud and abuse detection. Our work is crucial in maintaining the integrity of Uber's platform. The team employs advanced machine learning including LLMs and computer vision, knowledge graph, similarity search and reinforcement learning to monitor transactions, detect unusual patterns, and implement robust verification methods
</li><li>The Mobility Matching team at Uber plays a crucial role in developing and optimizing algorithms and systems that match supply (drivers) with demand (riders) in real-time. You will work on complex problems, leveraging data and build ML algorithms to ensure efficient and reliable marketplace matching. The team is broadly part of the Marketplace (PIMS) org, a central pillar to Uber's core technology which includes pricing, incentives/investments, matching, surge, etc. As the key brain of the company, we manage the complex dynamics of supply and demand, optimize dispatching algorithms, and continuously innovate to enhance the overall user experience for both riders and drivers. Improvements in these systems increase revenue in the hundreds of millions of dollars, and decrease wasted time of drivers and users. Your contributions will directly impact the experience of millions of users worldwide.
</li><li>The Rider Pricing and Incentives team at Uber plays a crucial role in developing and optimizing algorithms and systems that determine the trip prices, discounting and promotions for Uber riders worldwide. You will work on complex modeling, pricing and incentives targeting problems, leveraging data and building ML algorithms to ensure accurate and robust pricing models and successful pricing optimization outcomes. The team is broadly part of the Marketplace organization, a central pillar to Uber's core technology which more broadly includes pricing, incentives/investments, matching, surge, etc. As a key team within Uber, we manage the complex dynamics between short term optimized pricing and long-term optimized pricing, promotion targeting and continuously innovating to enhance the overall user experience for riders. Improvements in these systems increase revenue in the hundreds of millions of dollars, and positively impact the experience of millions of users worldwide, as well as their ability to get around in the world.
</li><li>Join our Capacity Planning team as a Ph.D. intern to drive the future of infrastructure resource management through advanced quantitative methods. You will be at the forefront of implementing our data-driven forecasting vision, moving away from reactive, manual processes to scalable, automated solutions that utilize predictive analytics and real-time utilization data. This is a high-impact opportunity to work with the Applied Science and Engineering teams on designing and optimizing the central intelligence systems for capacity planning. Your expertise will be crucial in developing granular, highly accurate resource forecasts, ensuring service reliability for unexpected demand, and making key decisions that directly influence financial accountability, operational agility, and optimal resource utilization across the entire platform.
</li><li>The Autonomous Vehicles Cloud team is dedicated to accelerating the autonomous vehicles industry to L4 by serving as a premier AV data leader. Recently, we announced a partnership with NVIDIA to jointly develop a data factory for autonomous vehicle development. The team includes engineers with diverse backgrounds in embedded software, cloud computing, batch data processing, and ML research. We are looking for talent passionate about autonomous vehicles and eager to make a significant impact.
</li><li>The Marketplace Signals team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals-such as eyeball ETA, spinner time, and supply reliability indicators-are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions.
</li><li>Applied AI is a horizontal AI team at Uber partnering with product and platform teams across the company to deliver cutting-edge machine learning solutions for core business problems. The Computer Vision team in AppliedAI specializes in Generative AI, Foundation Model, and classical Computer Vision solutions, and the ML infrastructure needed to scale these systems in production.
</li><li>Fabric Controller brings together platforms that keep large scale systems resilient and easy to operate, including Cadence and Repair Engine. Cadence is an open source workflow orchestration engine that manages distributed state, retries, scaling, and recovery so teams can focus on business logic while supporting mission critical workloads across many industries. Repair Engine detects, diagnoses, and remediates issues by correlating signals across infrastructure and application layers through an ingestion pipeline and statistical analysis. An ML engine is being developed to improve diagnostics by learning patterns from historic issues, reducing false positives, and incorporating broader context such as workload types and traffic trends. Together these systems strengthen reliability, automation, and operational efficiency across the stack.
</li></ul>What You'll Do
<ul><li>Drive exciting, ambitious, previously unsolved projects from end to end
</li><li>Develop novel algorithms that use Uber data at global scale
</li><li>Thrive in an environment with ambiguous product requirements
</li><li>Collaborate closely with product managers and data scientists
</li><li>Be motivated to independently own and drive projects forward
</li><li>Have a passion to make Uber better for our customers
</li></ul>Basic Qualifications
<ul><li>Currently enrolled in a Ph.D. program studying computer science, machine learning, data mining, artificial intelligence, constrained optimization, statistics, or a related quantitative field
</li><li>Candidates must have at least one semester/quarter of their education left following the internship
</li><li>Knowledge of underlying technical foundations of statistics, machine learning, optimization, systems, etc.
</li><li>Experience in one or more object-oriented languages, including C++, Java, Python, or Go
</li></ul>Preferred Qualifications
<ul><li>Ability to communicate effectively with both technical and business partners
</li><li>Experience in simplifying/converting business problems into technical problems
</li>Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation 
<li>
</li></ul> 
 
For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits.</div>

2026 PhD Software Engineer Intern (Machine Learning), United States

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. 
As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. 
This internship is not just about executing tasks &ndash; it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. 
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 
Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. 
 
Must be eligible and available for a full-time (40h/ week) 12 week internship between May 2026 and September 2026. 
 
Amazon has positions available in San Francisco, CA and Seattle, WA. 
 
The ideal candidate should possess: 
<ul><li>Strong background in machine learning, deep learning, and/or robotics</li><li>Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR.</li><li>Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models.</li><li>Proficiency in Python, Experience with PyTorch or JAX</li><li>Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team</li></ul> 
Apply now and embark on an extraordinary journey of discovery and innovation! 
 
Key job responsibilities 
<ul><li>Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics</li><li>Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control</li><li>Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning</li><li>Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a PhD</li><li>Can relocate to where the internship is based</li><li>Experience programming in Java, C++, Python or related language</li><li>Must be available for full-time (40 hours per week) internship for the whole duration of the internship</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Experience in designing experiments and statistical analysis of results</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
 
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics

Aldea Inc

<div>About Aldea
Aldea is a multi-modal foundational AI company reimagining the scaling laws of intelligence. We believe today's architectures create unnecessary bottlenecks for the evolution of software. Our mission is to build the next generation of foundational models that power a more expressive, contextual, and intelligent human&ndash;machine interface. 
The Role
We are hiring a Research Engineer (Machine Learning) to build the infrastructure that powers Aldea's multi-modal AI research. You will design, optimize, and scale the training and inference systems that enable our research team to explore next-generation architectures across language, speech, and multi-modal domains. 
This is a high-leverage role where your work directly enables breakthrough research. You'll build production-grade systems supporting rapid experimentation at billion-parameter scale and real-time deployment of speech and language models. If you're passionate about building the systems that accelerate AI research, this role is for you. 
What You'll Do<ul><li>
Build and maintain distributed training infrastructure supporting researchers across language and speech domains at a billion-plus-parameter scale.</li><li>
Optimize training and inference performance across the stack, delivering significant speedups through framework optimization, custom kernels, and system-level improvements.</li><li>
Design experiment infrastructure including automated evaluation pipelines, experiment tracking, and monitoring systems that enable rapid iteration.</li><li>
Scale infrastructure from single-node to multi-node distributed training and deploy production inference systems for real-time applications.</li><li>
Support researchers with fast turnaround on infrastructure issues and maintain high reliability across all systems.</li><li>
Collaborate with research scientists, data engineers, and leadership to define technical priorities and infrastructure roadmap.</li></ul>
Minimum Qualifications<ul><li>
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.</li><li>
3+ years of experience with PyTorch and distributed training frameworks (DDP, FSDP, DeepSpeed, or similar).</li><li>
Experience training large-scale deep learning models at 1B+ parameters.</li><li>
Deep understanding of training optimization techniques including mixed precision, gradient checkpointing, and memory management.</li><li>
Proven ability to build production-grade ML infrastructure with high reliability.</li><li>
Track record of delivering significant performance optimizations in ML training or inference systems.</li></ul>
Preferred Qualifications<ul><li>
Experience with custom kernel development (CUDA, Triton) or GPU optimization.</li><li>
Hands-on experience with large-scale pretraining (100B+ tokens, ideally trillion+ scale).</li><li>
Experience optimizing inference for production: quantization, vLLM, TensorRT, or custom serving engines.</li><li>
Familiarity with speech/audio ML systems and real-time inference constraints.</li><li>
Experience building automated evaluation frameworks and experiment tracking systems.</li><li>
Knowledge of profiling tools and multi-node training across 8-32+ GPUs.</li><li>
Exposure to job orchestration systems (SLURM, Kubernetes, Ray).</li><li>
Master's or PhD in Computer Science, Machine Learning, or related field.</li></ul>
Compensation &amp; Benefits<ul><li>
Competitive base salary</li><li>
Performance-based bonus aligned with research and model milestones</li><li>
Equity participation</li><li>
Comprehensive health, dental, and vision coverage</li><li>
Flexible paid time off</li></ul> 
Aldea is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics. 
Aldea uses E-Verify to confirm employment eligibility in compliance with federal law. For more information please visit: https://www.e-verify.gov. 
Please note: We do not accept unsolicited resumes from recruiters or employment agencies and will not be responsible for any fees related to unsolicited resumes.</div>

Research Engineer (Machine Learning)

Snap Inc.

<div>
 Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company&rsquo;s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.
 
 
 Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We&rsquo;re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
 
 
 We&rsquo;re looking for a Backend Engineer to join Snap Inc!
 
 
 What you&rsquo;ll do:
 
 
 <ul>
 <li>
 Design, implement, and operate our most critical and scalable services - ranging from user identity services, friend graph, and our core persistence layer
 </li>
 <li>
 Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products
 </li>
 <li>
 You evaluate, appropriately test, and debug your work, striving for high quality
 </li>
 <li>
 Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
 
 
 </li>
 </ul>
 Knowledge, Skills &amp; Abilities:
 
 
 <ul>
 <li>
 Experience with backend services or distributed systems
 </li>
 <li>
 Proven track record of operating highly-available systems at significant scale
 </li>
 <li>
 You can independently execute on medium sized features, taking a few weeks and multiple PRs to complete
 </li>
 <li>
 You understand the operational aspects of your system and may participate in incident or hotfix investigation and resolution
 </li>
 <li>
 Ability to collaborate and work well with others
 </li>
 <li>
 Experience in at least one of the following areas:
 </li>
 <li>
 Large-scale microservices and distributed systems
 </li>
 <li>
 Cloud computing and storage systems
 </li>
 <li>
 Infrastructure and large-scale system design
 </li>
 <li>
 Security
 </li>
 <li>
 Networking and data storage
 </li>
 <li>
 Machine learning and natural language processing tools
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 2+ years of post-Bachelor&rsquo;s software development experience; or Master&rsquo;s degree in a technical field + 1+ year of post-grad software development experience; or PhD in a relevant technical field
 </li>
 <li>
 Experience working with distributed systems
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Experience with Java, C++, and/or Python
 </li>
 <li>
 Experience with NoSQL solutions, Memcache/Redis, Kubernetes, or Google/AWS services
 
 
 </li>
 </ul>
 If you have a disability or special need that requires accommodation, please don&rsquo;t be shy and provide us some information.
 
 
 "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a &ldquo;default together&rdquo; approach and expect our team members to work in an office 4+ days per week.
 
 
 At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
 
 
 We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
 
 
 Our Benefits: Snap Inc. is its own community, so we&rsquo;ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap&rsquo;s long-term success!
 
 
 
 Compensation
 
 
 
 In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate&rsquo;s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
 
 
 Zone A (CA, WA, NYC):
 
 
 The base salary range for this position is $157,000-$235,000 annually.
 
 
 Zone B:
 
 
 The base salary range for this position is $149,000-$223,000 annually.
 
 
 Zone C:
 
 
 The base salary range for this position is $133,000-$200,000 annually.
 
 
 This position is eligible for equity in the form of RSUs.
</div>

Software Engineer, Backend, Level 4

Andromeda Robotics

<div><h3 class="jobSectionHeader">About Us</h3>
Andromeda Robotics is an ambitious social robotics company with offices in Melbourne and San Francisco, dedicated to creating robots that seamlessly and intelligently interact with the human world. Our first robot, Abi, is a testament to this vision&mdash;a custom-built platform designed from the ground up to be a helpful aid and intuitive partner in aged care homes. We are a passionate, collaborative team of engineers who solve some of the most challenging problems in AI and robotics. To accelerate our development and ensure Abi's reliability, we are seeking a foundational member to build out our capabilities to train and test our robot in simulation.<h3 class="jobSectionHeader">
Our Values</h3>
Deeply empathetic - Kindness and compassion are at the heart of everything we do.
Purposely playful - Play sharpens focus. It keeps us curious, fast and obsessed with the craft.
Relentlessly striving - With relentless ambition, an action bias and constant curiosity, we don&rsquo;t settle.
Strong when it counts - Tenacious under pressure, we expect problems and stay in motion to adapt and progress.
United in action - Different minds. Shared mission. No passengers.<h3 class="jobSectionHeader">
The Role</h3>
We are looking for a creative and driven Simulation and Test Engineer to build Andromeda's testing infrastructure for our conversational AI systems and embodied character behaviours. Your immediate focus will be creating robust test systems for Abi's voice-to-voice chatbot, social awareness perception, and gesture motor control. As this infrastructure matures, you'll extend it into simulation environments for generating synthetic training data for character animation and gesture models.<h3 class="jobSectionHeader">
The Team</h3>
You'll work at the intersection of our character software, robotics, perception, conversational AI, controls, and audio engineering teams. We bring deep expertise from autonomous vehicles and robotics, including simulation backgrounds. You'll collaborate with product owners and technical specialists to define requirements, integrate systems, and ensure quality across our AI/ML stack.
Requirements<h3 class="jobSectionHeader">
Phase 1: Build The Test Foundation</h3><ul>
<li>Define and stand up synthetic test environments for our AI/ML conversational stack</li>
<li>Conversational AI testing: voice-to-voice chat quality, response appropriateness, tool calling accuracy</li>
<li>Memory system testing: context retention, recall accuracy, conversation coherence</li>
<li>Audio modelling and testing: multi-speaker scenarios, room acoustics, voice activity detection</li>
<li>Perception system testing: social awareness (face detection, gaze tracking, person tracking)</li>
<li>Gesture appropriateness testing: Working with our Controls/ML team, create test infrastructure to validate that Abi's body gestures</li>
<li>CI/CD and automated regression testing for all AI/ML subsystems</li>
<li>Custodian of quality metrics: if they don't exist, work with stakeholders to elicit use cases, derive requirements, and establish measurable quality metrics</li>
<li>Requirements formalisation: you're skilled at gathering, documenting, and tracing requirements back to test cases</li>
</ul><h3 class="jobSectionHeader">Phase 2: Scale To ML Training Infrastructure</h3>
Our approach to gesture generation requires high-fidelity synthetic interaction data at scale. You'll investigate and build the infrastructure to generate this data, working closely with our character software team to define requirements and validate approaches.<ul>
<li>
Extend test environments into training data generation pipelines</li>
<li>Investigate and stand up simulation tools (e.g. Unity, Unreal Engine, Isaac Sim) to support our machine learning pipeline with synthetic data and validation infrastructure</li>
<li>Build infrastructure for fine-tuning character animation models on simulated multi-actor scenarios</li>
<li>Enable ML-generated gesture development to augment hand-crafted animation workflows</li>
<li>Create virtual environments with diverse social interaction scenarios for training and evaluation</li>
</ul><h3 class="jobSectionHeader">Success In This Role Looks Like</h3>
Months 1-3, stabilise our conversational system with automated regression tests and measurable quality benchmarks. By month 6, deliver an integrated simulation environment enabling rapid testing and iteration across our AI/ML stack.
You'll design tests that push our systems beyond their limits and find what's brittle. Through trade studies and make-vs-buy decisions, you'll establish the infrastructure, set up automatic regression tests, and trace test cases back to high-level requirements. You'll be the final guardian, verifying that our AI and machine learning systems work as intended before integration with Abi's physical platform. Your work will directly impact the speed and quality of our development, ensuring that every software build is robust, reliable, and safe.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul>
<li>Architect and Build: Design, develop, and maintain scalable test infrastructure for conversational AI, perception, and gesture control systems</li>
<li>Own Testing Pipeline: Develop a robust CI/CD pipeline for automated regression testing, enabling rapid iteration and guaranteeing quality before deployment</li>
<li>Develop Test Scenarios: Create diverse audio environments, multi-actor social scenarios, and edge cases to rigorously test Abi's conversational and social capabilities</li>
<li>Model with Fidelity: Implement accurate models of Abi's hardware stack (cameras, microphone array, upper body motion) as needed for test and simulation scenarios</li>
<li>Enable Future ML Training: Design test infrastructure with an eye towards evolution into a simulation platform for generating synthetic training data for character animation and gesture models</li>
<li>Integrate and Collaborate: Work closely with the robotics, AI, and software teams to seamlessly integrate their stacks into the test infrastructure and define testing requirements</li>
<li>Analyse and Improve: Develop metrics, tools, and dashboards to analyse test data, identify bugs, track performance, and provide actionable feedback to the engineering teams</li>
</ul><h3 class="jobSectionHeader">Ideally You Have</h3><ul>
<li>Bachelor or Masters in Computer Science, Robotics, Engineering, or a related field</li>
<li>5+ years of professional experience testing complex AI/ML systems (conversational AI, perception systems, or embodied AI)</li>
<li>Strong programming proficiency in Python (essential); C++ experience valuable</li>
<li>Hands-on experience with LLM testing, voice AI systems, or chatbot evaluation frameworks</li>
<li>Understanding of audio processing, speech recognition, and/or computer vision fundamentals</li>
<li>Experience with testing frameworks and CI/CD tools (pytest, Jenkins, GitHub Actions, etc.)</li>
<li>Familiarity with ML evaluation metrics and experimental design</li>
<li>A proactive, first-principles thinker who is excited by the prospect of owning a critical system at an early-stage startup</li>
</ul><h3 class="jobSectionHeader">Bonus Points</h3><ul>
<li>Experience with simulation platforms (e.g. Unity, Unreal Engine, NVIDIA Isaac Sim, Gazebo) and physics engines</li>
<li>Experience with character animation systems, motion capture data, or gesture generation</li>
<li>Knowledge of reinforcement learning, imitation learning, or synthetic data generation for training ML models</li>
<li>Experience with 3D modelling tools and game engine content creation</li>
<li>Understanding of ROS2 for robotics integration</li>
<li>Knowledge of sensor modelling techniques for cameras and audio</li>
<li>Experience building and managing large-scale, cloud-based simulation infrastructure</li>
<li>PhD in a relevant field</li>
</ul>
Benefits
The expected base salary range for this role, when performed in our San Francisco office, is $150,000 - $250,000 USD, depending on skills and experience. The salary for this position may vary depending on factors such as job-related knowledge, skills, and experience. The total compensation package may also include additional benefits or components based on the specific role. Details will be provided if an employment offer is made.
If you&rsquo;re excited about this role but don&rsquo;t meet every requirement, that&rsquo;s okay&mdash;we encourage you to apply. At Andromeda Robotics, we celebrate diversity and are committed to creating an inclusive environment for all employees. Let&rsquo;s build the future together.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.</div>

Simulation and Test Engineer (Conversational AI) - US Based

Samsara

<div><div>Who we are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations&trade; Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing &mdash; and we are excited to help digitally transform their operations at scale.

Working at Samsara means you'll help define the future of physical operations and be on a team that's shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you'll have the autonomy and support to make an impact as we build for the long term.</div>
About the role:

The Samsara AI team builds end-to-end AI solutions for our customers as well as core ML infrastructure for Samsara. As a Staff Machine Learning Engineer, you will be working with petabyte-scale sensor, diagnostic, video, and text data to solve critical problems for Physical Operations customers, globally. You will work closely with ML Engineers and Scientists, as well as full-stack and firmware engineers to deliver core product features, services, and optimizations.

This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role.

You should apply if:
<ul>
<li>You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact&mdash;helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.</li>
<li>You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.</li>
<li>You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.</li>
<li>You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.</li>
<li>You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we're all racing toward our connected operations vision, and we intend to win&mdash;together.</li>
</ul><h4 class="jobSectionHeader">In this role, you will:</h4>
<ul><li>Lead design and implementation of critical AI product initiatives on Edge devices.</li>
<li>Develop both tactical AI solutions as well as more strategic and longer term research.</li>
<li>Work with petabyte-scale data from customer operations including text, transactions, diagnostics, sensor, camera, and location data.</li>
<li>Partner across business units to explore and prototype new AI experiences and optimize the ML model performance on edge devices.</li>
<li>Stay connected to industry and academic research and adopt novel technology that suits Samsara's needs.</li>
<li>Champion, role model, and embed Samsara's cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices</li>
</ul>
Minimum requirements for the role:
<ul>
<li>8+ years experience as a Machine Learning Engineer.</li>
<li>Profound experience in optimizing ML models and systems for Edge compute constraints.</li>
<li>Proficient with Spark, Ray, or a similar framework.</li>
<li>Coding in python or similar.</li>
<li>Coding in C++ or Rust.</li>
<li>Strong functional knowledge of the iterative machine learning product development process.</li>
<li>Experienced in developing and shipping production code at large scale.</li>
<li>Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions.</li>
<li>Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge.</li>
<li>Experience coaching and mentoring ML Engineers.</li>
</ul>
An ideal candidate also has:
<ul>
<li>Proficiency in self-serving with data for experiments and model training at scale.</li>
<li>An established record of successful high impact deliveries in AI.</li>
<li>Deep knowledge in state of the art Computer Vision and multi-model models.</li>
</ul><div>
At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact.

Benefits

Full time employees receive a competitive total compensation package along with employee-led remote and flexible working, health benefits, and much, much more. Take a look at our Benefits site to learn more.

Accommodations

Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process.

Flexible Working

At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual's ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.

Fraudulent Employment Offers

Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in '@samsara.com' or '@us-greenhouse-mail.io'. For more information regarding fraudulent employment offers, please visit our blog post here.</div></div>

Staff Machine Learning Engineer

Delty (YC X25)

<div>
 
 About Us
 
 
 
 
 Delty is building the world&rsquo;s first &ldquo;AI Staff Engineer.&rdquo;
 
 Unlike typical code-generation tools, Delty is trained on a team&rsquo;s codebase, documentation, and system history &mdash; giving it a system-level understanding of architecture, conventions, and constraints. Delty helps engineering teams design enterprise-scale software systems, make architectural decisions, and enable AI coding agents to work with real system context.
 
 
 Delty was founded by former engineering leaders from
 
 Google, including co-founders with deep experience at YouTube and in large-scale infrastructure
 
 . You&rsquo;ll get to work alongside people who built massive systems at scale &mdash; a chance to learn a
 
 lot
 
 and contribute meaningfully from day one.
 
 
 We believe in solving hard problems together as a team, iterating quickly, and building software with long-term thinking and ownership.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Work full-stack: design and build features spanning front-end, back-end, data storage and processing.
 </li>
 <li>
 Build new product modules and services from scratch &mdash; or evolve existing ones &mdash; guided by context-aware system design.
 </li>
 <li>
 Work with AI and machine learning: integrate large-language models (LLMs), process large or long-form text data, apply traditional ML (e.g. regression, data pipelines), and build tooling around AI-driven flows.
 </li>
 <li>
 Make architectural decisions &mdash; choose frameworks, data models, APIs, storage solutions &mdash; balancing trade-offs between performance, scalability, maintainability, and complexity.
 </li>
 <li>
 Collaborate closely with co-founders and other engineers to translate product vision into a working, maintainable codebase.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 At least 3 years of full-stack engineering experience, including substantial work with AI/ML.
 </li>
 <li>
 Strong skills across front-end, back-end, databases/data storage &mdash; and demonstrated ability to design end-to-end systems.
 </li>
 <li>
 Experience working with or integrating AI/ML &mdash; LLMs, data pipelines, long-form text processing, traditional ML like regression or statistical modeling.
 </li>
 <li>
 Good design sense and architectural thinking: you understand trade-offs (scalability vs complexity, speed vs maintainability) and can choose wisely based on constraints.
 </li>
 <li>
 Comfort working in a fast-paced startup-style environment: nimble, iterative, high ownership.
 </li>
 <li>
 Bonus: prior startup experience, or even having been a founder &mdash; we value entrepreneurial thinking, self-direction, and willingness to wear multiple hats.
 
 
 </li>
 </ul>
 Why join
 
 
 <ul>
 <li>
 Learn from seasoned Google engineers: As former Google engineers who built systems at YouTube and Google Pay, we&rsquo;ve operated at massive scale. Working alongside us gives you a chance to build similar systems and learn best practices, scale thinking, and software design deeply.
 </li>
 <li>
 High impact: At a small but ambitious team, your contributions will influence architecture, product direction, and core features. You will have real ownership and see the effects of your work quickly.
 </li>
 <li>
 Grow fast: We&rsquo;re iterating rapidly; you&rsquo;ll be exposed to the full stack, AI/ML pipelines, system architecture, data modeling, and product-level decisions &mdash; a fast-track to becoming a senior engineer or technical lead.
 </li>
 <li>
 Challenging and meaningful work: We&rsquo;re tackling the hardest part of software engineering: bridging AI-generated prototypes and robust, scalable enterprise-grade systems. If you enjoy thinking deeply about systems and building reliable, maintainable foundations &mdash; this is for you.
 </li>
 </ul>
</div>

Full stack software engineer

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