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ai engineer

Loop

<div>
 
 About Loop
 
 
 
 Loop is on a mission to unlock profits trapped in the supply chain (https://loop.com/article/unlock-profit-trapped-in-your-supply-chain) and lower costs for consumers. Bad data and inefficient workflows create friction that limits working capital and raises costs for every supply chain stakeholder.
 
 
 Loop&rsquo;s modern audit and pay platform uses our domain-driven AI to harness the complexity of supply chain data and documentation. We improve transportation spend visibility so companies can control their costs and power profit. That is why industry leaders like J.P. Morgan Chase, Great Dane, Emerge, and Loadsmart work with Loop.
 
 
 Our investors include J.P. Morgan, Index Ventures, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, Rakuten, and long-standing industry leaders like C.H. Robinson.
 
 
 
 About The Role
 
 
 
 Loop is growing its AI team and you&rsquo;ll have the opportunity to build both AI models and features that directly impact Loop&rsquo;s business. Loop is positioned to disrupt the incumbent freight audit and pay market, and is one of the companies leading the AI services wave, utilizing AI to automate complex back-office workflows and tasks. You will face and solve many complex technical challenges while you receive guidance and feedback from the team. The range of work here is broad, you can work on everything from training and deploying in-house multimodal LLMs, scaling our inference infrastructure, or building out and shipping agentic workflows. In doing so, you&rsquo;ll have the opportunity to define how the AI and broader Loop team will grow.
 
 
 
 What you will work on
 
 
 
 Our primary focus has been on document extraction and understanding, where we utilize multimodal LLMs, including our own in-house foundation model, to extract, normalize, and link data together into our domain model. As Loop&rsquo;s customers rely on Loop to ingest and normalize highly accurate data, we hold ourselves to a high standard to build models with a very high level of accuracy. In tandem, Loop&rsquo;s machine learning platform requires a high degree of reliability and scalability, and we expect our training and inference volume to scale several orders of magnitude in the coming year. Going forward, Loop will expand its AI capabilities, expanding into other areas such as workflow automation and audit, where we will utilize agents to tackle these problems.
 
 
 This role spans multiple domains:
 
 
 <ul>
 <li>
 ML modeling &ndash; training, evaluating, and deploying models.
 </li>
 <li>
 AI engineering &ndash; utilizing and orchestrating API LLM models to build agents to solve business problems at Loop.
 </li>
 <li>
 Backend engineering &ndash; building out frameworks to enable AI agents at scale.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 1+ years of hands-on experience in deep learning frameworks (e.g., PyTorch, Tensorflow, etc.) or shipping agents to production.
 </li>
 <li>
 Solid understanding of fundamental ML algorithms, especially multimodal LLMs.
 </li>
 <li>
 Experience fine-tuning LLMs and deploying them to production or building out agentic systems.
 </li>
 <li>
 Ability to ship high-quality code to production.
 </li>
 <li>
 Experience in cloud environments (AWS, Google, Azure).
 </li>
 <li>
 Strong communication skills and willingness to collaborate in a cross-functional team environment with domain experts.
 </li>
 <li>
 Keep up to date with the latest AI research.
 </li>
 <li>
 Ability to work in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 <ul>
 <li>
 Base pay 130k - 200k
 
 
 </li>
 </ul>
 
 Benefits &amp; Perks
 
 
 
 <ul>
 <li>
 Premium Medical, Dental, and Vision Insurance plans
 </li>
 <li>
 Insurance premiums covered 100% for you
 </li>
 <li>
 Unlimited PTO
 </li>
 <li>
 Fireside chats with industry leading keynote speakers
 </li>
 <li>
 Off-sites in locales such as Napa and Tahoe
 </li>
 <li>
 Generous professional development budget to feed your curiosity
 </li>
 <li>
 Physical and Mental fitness subsidies for yoga, meditation, gym, or ski memberships
 </li>
 </ul>
</div>

AI Engineer

Andiamo

<div>
 Generative AI Engineer - Pre-IPO Tech Company
 
 
 
 About The Role
 
 
 
 We are seeking a talented
 
 Generative AI Engineer
 
 to help design and build the next generation of AI-powered applications at a high-growth, pre-IPO technology company. You will work on applying large language models (LLMs), multimodal AI, and cutting-edge generative techniques to create products that transform how our customers interact with data, content, and decision-making systems.
 
 
 This is a hands-on engineering role at the intersection of AI research and scalable product development. You will collaborate with data scientists, ML engineers, and product managers to prototype, deploy, and optimize generative AI systems that deliver measurable customer and business impact.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Develop Generative Applications: Build production-ready systems leveraging LLMs and generative models for NLP, code, and multimodal use cases.
 </li>
 <li>
 Integrate with Products: Design APIs and services that embed generative AI capabilities into customer-facing applications.
 </li>
 <li>
 Optimize Models: Fine-tune, distill, and adapt foundation models to specific tasks and domains for efficiency and performance.
 </li>
 <li>
 Leverage Retrieval &amp; Memory: Implement retrieval-augmented generation (RAG), vector search, and embeddings for context-aware AI solutions.
 </li>
 <li>
 Ensure Reliability: Build monitoring and evaluation pipelines to track model quality, detect drift, and maintain trustworthiness in production.
 </li>
 <li>
 Collaborate Cross-Functionally: Work with researchers and product leaders to translate cutting-edge AI into practical features.
 </li>
 <li>
 Stay Ahead: Keep current with state-of-the-art generative AI research and frameworks, bringing new ideas and approaches into the company.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 Professional Experience: 3-7 years in applied ML/AI engineering, with at least 1-2 years working on generative AI, LLMs, or related areas.
 </li>
 <li>
 Technical Skills: Proficiency in Python, strong experience with ML/AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex).
 </li>
 <li>
 LLM Experience: Hands-on experience fine-tuning or deploying large language models, and familiarity with APIs such as OpenAI, Anthropic, or similar.
 </li>
 <li>
 Infrastructure Knowledge: Experience with cloud ML platforms (AWS Sagemaker, GCP Vertex AI, Azure ML) and vector databases (Pinecone, Weaviate, Milvus, FAISS).
 </li>
 <li>
 Systems Thinking: Ability to design scalable pipelines for training, inference, and integration into production systems.
 </li>
 <li>
 Collaboration: Strong communication skills and ability to partner across engineering, product, and research teams.
 </li>
 <li>
 Education: Bachelor&rsquo;s or Master&rsquo;s in Computer Science, Engineering, AI/ML, or a related field; PhD a plus.
 
 
 </li>
 </ul>
 Why Join
 
 
 This is a unique opportunity to shape the future of generative AI at a pre-IPO company with $500M+ in funding. As a Generative AI Engineer, you&rsquo;ll work with state-of-the-art models, solve complex problems at scale, and bring transformative AI capabilities directly to customers. You&rsquo;ll be part of a high-growth team where innovation is encouraged, impact is immediate, and the future of AI is being built.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

AI/Generative AI Engineer

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor's degree or equivalent practical experience. 
</li>
<li>2 years of experience with security assessments or security design reviews or threat modeling. 
</li>
<li>2 years of experience with security engineering, computer and network security and security protocols. 
</li>
<li>2 years of coding experience in one or more general purpose languages.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Expertise in the AI security space, including research, exploits, and mitigations</li>
<li>Proficiency in programming for security research tasks such as scripting, tool development, and data analysis</li>
<li>Understanding of threat modeling, risk assessments or security assessments of products.</li>
<li>Ability to read, understand, and analyze code as well as write small tools and scripts</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Our Security team works to create and maintain the safest operating environment for Google's users and developers. Security Engineers work with network equipment and actively monitor our systems for attacks and intrusions. In this role, you will also work with software engineers to proactively identify and fix security flaws and vulnerabilities.

As an AI Information Security Engineer, you will help to ensure that our AI products and systems are designed and implemented to the security standards. You will perform technical security assessments, code reviews and vulnerability testing to highlight risk, helping Google teams and partners to improve security, and work on a wide variety of software designs and technology stacks. You will also work closely with other Google Engineers to design and build proactive methods to enhance our security posture. In addition, you will have the option to specialize or perform research in a number of varying fields.<div> 
The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.</div><div></div><div> 
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li><div><div><div>Analyze systems to identify vulnerabilities and opportunities for hardening, and report findings to stakeholders for mitigation.</div></div></div></li>
<li>Promote quality security practices across the organization, influencing software engineers, immediate colleagues, and beyond Google.</li>
<li><div><div><div>Perform rapid threat modeling of complex systems to quickly determine areas that warrant further investigation and security review.</div></div></div></li>
<li>Conduct research to identify and mitigate entire classes of vulnerabilities. Leverage AI tools and agents in your day-to-day work to scale your own capabilities.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is 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. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI Security Engineer

Handshake

<div><h1 class="jobSectionHeader">About Handshake</h1>
Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
Why join Handshake now:<ul><li>
Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel</li><li>
Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions</li><li>
Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others</li><li>
Build a massive, fast-growing business with billions in revenue</li></ul><h1 class="jobSectionHeader">
About the Role
</h1>Handshake is hiring an Associate Machine Learning Engineer for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative, responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities. In this role, you will contribute directly to this mission by developing, deploying, and enhancing machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.
You'll join a high-impact team leveraging cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers built upon a robust data platform with billions of data points. Your work will drive critical marketplace metrics, enhance user engagement, and contribute to responsible AI practices around explainability, fairness, and quality.
What You'll Do<ul><li>
Innovator: Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization &mdash; with guidance from senior engineers.</li><li>
Collaborator: Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.</li><li>
Learner: Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.</li></ul><h1 class="jobSectionHeader">
Desired Capabilities
</h1><ul><li>Bachelor&rsquo;s degree in Computer Science, Data Science, or a related field</li><li>
0&ndash;2 years of experience in machine learning, data science, or a related area</li><li>
Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow</li><li>
Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation</li></ul>
Extra Credit<ul><li>
Master&rsquo;s degree or currently pursuing an advanced degree in a relevant field</li><li>
Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI</li><li>
Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)</li><li>
Experience with cloud platforms (GCP, AWS, or Azure)</li><li>
Clear communicator, able to translate technical work for diverse audiences</li><li>
Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams</li></ul><h1 class="jobSectionHeader">
Perks</h1>
Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
The below benefits are for full-time US employees.
Ownership: Equity in a fast-growing company
Financial Wellness: 401(k) match, competitive compensation, financial coaching
Family Support: Paid parental leave, fertility benefits, parental coaching
Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
Growth: $2,000 learning stipend, ongoing development
Remote &amp; Office: Internet, commuting, and free lunch/gym in our SF office
Time Off: Flexible PTO, 15 holidays + 2 flex days
Connection: Team outings &amp; referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
Compensation Range: $115K - $144K</div>

Associate Machine Learning Engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Join the next revolution in robotics at Amazon's Frontier AI &amp; Robotics team, where you'll work alongside world-renowned AI pioneers like Pieter Abbeel, Rocky Duan, and Peter Chen to make breakthrough foundation models run at production scale. As a Senior Machine Learning Engineer embedded in our science team, you'll be instrumental in transforming innovative research into high-performance production systems. You'll collaborate directly with scientists to optimize large-scale transformer architectures for robotics applications, leveraging your expertise in CUDA and TensorRT to achieve unprecedented inference efficiency at Amazon scale. 
 
In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up. You'll leverage NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications. 
 
Key job responsibilities 
<ul><li>Drive inference optimization strategies for large-scale foundation models using TensorRT, CUDA, and other NVIDIA tools</li><li>Collaborate closely with scientists to influence model architectures for optimal hardware utilization</li><li>Design and implement efficient compilation pipelines for complex transformer architectures</li><li>Develop comprehensive benchmarking frameworks to measure and optimize model performance</li><li>Build robust monitoring solutions to ensure reliable model serving at scale</li><li>Explore and evaluate emerging optimization techniques including ONNX Runtime and other ML compilers</li><li>Maintain high engineering standards through proper testing, documentation, and code review practices</li></ul> 
A day in the life 
<ul><li>Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques</li><li>Partner with scientists to analyze model architectures and propose efficiency improvements</li><li>Implement and benchmark various optimization strategies for large-scale models</li><li>Debug performance bottlenecks using NVIDIA profiling tools</li><li>Participate in technical discussions about new model architectures with the science team</li><li>Design and maintain performance monitoring systems for production deployment</li><li>Prototype new acceleration approaches using emerging compilation frameworks</li></ul> 
About the team 
At Frontier AI &amp; Robotics, we're not just advancing robotics &ndash; we're reimagining it from the ground up. Our team, led by pioneering AI researchers Pieter Abbeel, Rocky Duan, and Peter Chen, is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. 
What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence &ndash; from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. 
 
Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>Bachelor's degree in computer science or equivalent</li><li>5+ years of non-internship professional software development experience</li><li>5+ years of programming with at least one software programming language experience</li><li>5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience as a mentor, tech lead or leading an engineering team</li><li>Strong expertise in Python, C++ and CUDA programming</li><li>Experience with TensorRT or similar ML optimization frameworks</li><li>Track record of optimizing ML models for production</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Expertise in NVIDIA's ML stack (cuDNN, CUDA Graph, etc.)</li><li>Experience with ML compilers (ONNX Runtime, TVM, etc.)</li><li>Experience with transformer model optimization</li><li>Background in performance profiling and optimization</li><li>Experience working directly with research teams</li><li>Track record of building robust monitoring systems</li><li>Experience with large-scale ML serving systems</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. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 193,300.00 - 261,500.00 USD annually 
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually</div>

Sr. Software Development Engineer, Frontier AI & Robotics

Giga

<div>
 
 About Giga
 
 
 
 Giga has recently raised a $61M Series A and has several paying customers, including DoorDash. We&rsquo;re building the next generation of customer experience &mdash; real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world&rsquo;s largest enterprises.
 
 
 It&rsquo;s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.
 
 
 The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:
 
 
 <ul>
 <li>
 Voice AI startup Giga raises $61M Series A
 </li>
 <li>
 DoorDash and Giga Partnership
 
 
 </li>
 </ul>
 Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!
 
 
 
 The Role
 
 
 
 We're looking for new grad engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers.
 
 
 This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.
 
 
 
 What You'll Work On
 
 
 
 You'll contribute to projects across our stack. Some examples:
 
 
 <ul>
 <li>
 Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
 </li>
 <li>
 Activity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behavior
 </li>
 <li>
 Dynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pages
 </li>
 <li>
 Agent memory: Conversation awareness and recent interaction lookups so agents remember context across sessions
 
 
 </li>
 </ul>
 You'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.
 
 
 
 You Might Be a Fit If You
 
 
 
 <ul>
 <li>
 Are graduating (or recently graduated) with a CS degree or equivalent background
 </li>
 <li>
 Have internship experience or significant projects where you wrote production-quality code
 </li>
 <li>
 Can take a problem, figure out an approach, and unblock yourself when you get stuck
 </li>
 <li>
 Prefer shipping over perfection but still care about quality
 </li>
 <li>
 Want to work at a startup where you'll have real responsibility early
 
 
 </li>
 </ul>
 
 Perks &amp; Benefits
 
 
 
 <ul>
 <li>
 Catered lunch daily
 </li>
 <li>
 Dinner stipend
 </li>
 <li>
 $150/month wellness benefit (gym, fitness classes, mental health)
 </li>
 <li>
 401(k) plan
 </li>
 <li>
 Commuter benefits
 </li>
 <li>
 Medical, dental, and vision coverage
 
 
 </li>
 </ul>
 Giga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
 
 
 Compensation Range: $160K - $250K
 
 
</div>

Software Engineer (New Grads) - San Francisco

Stealth Startup

<div>
 
 The Culture We Are Building
 
 <ul>
 <li>
 We are assembling a lean group of generalists. While we welcome experience, we're primarily looking for creative, curious problem solvers with a keen interest in open-ended, technically challenging problems.
 </li>
 <li>
 We are looking to hire in-person in San Francisco. We believe that having a community is critical for learning, growth, and camaraderie. We will pay generously for relocation assistance.
 </li>
 <li>
 We want to invest heavily in our team's growth. We will happily sponsor conference attendance and encourage projects and research. If there's something that will help you grow as an engineer, researcher, or designer, we actively want to support it.
 </li>
 <li>
 We believe in compensating exceptional talent exceptionally well. We are an early stage company, but are committed to working with candidates we're excited about to ensure they are excited too.
 </li>
 <li>
 We have an academic as well as competitive spirit. We enjoy thought exercises, math puzzles, intellectual inquiry, and vigorous debates.
 </li>
 </ul>
 
 
 
 
 Role: Machine Learning Engineer
 
 
 Design, train, and ship models that guide reviewers to the most important changes, resolve merge conflicts more safely, and make diffs understandable through semantic grouping and summarization. You'll combine retrieval, code‑aware modeling, and small‑model techniques to deliver low‑latency, cost‑effective ML in production.
 
 
 Responsibilities
 
 <ul>
 <li>
 -Train and fine‑tune models that predict the next location a reviewer should focus on: ranking files, hunks, and comments
 </li>
 <li>
 -Build ML‑assisted merge conflict resolution: align and reconcile hunks using code context/AST, propose safe resolutions, and explain changes
 </li>
 <li>
 -Develop semantic change grouping and diff visualization: detect refactors/moves, cluster related edits across files, and generate concise summaries
 </li>
 <li>
 -Evaluate retrieval and RAG for pull requests: retrieve relevant context, discussions, and history to improve grouping, prioritization, and summarization
 </li>
 <li>
 -Design offline/online evaluation: labeled datasets, ranking metrics (e.g., MAP/NDCG), A/B experiments, and human‑in‑the‑loop feedback
 </li>
 <li>
 -Operate efficient inference: apply small‑model techniques (LoRA, supervised fine‑tuning, distillation, quantization)
 </li>
 </ul>
 
 Qualifications
 
 <ul>
 <li>
 -Strong background in deep learning research and implementation, with experience in modern architectures and concepts (transformers, MoE, reasoning, etc.)
 </li>
 <li>
 -Track record publishing results at top-tier conferences (NeurIPS, ICML, ICLR)
 </li>
 <li>
 -Expertise in Python and ML frameworks (PyTorch, JAX)
 </li>
 <li>
 -Experience with MLOps and model optimization (ONNX, TensorRT, serving infrastructure)
 </li>
 <li>
 -Familiarity with cost‑effective techniques: LoRA, supervised fine‑tuning, distillation, and quantization for small/efficient models
 </li>
 <li>
 -Familiarity with systems programming across the stack: Rust/C/C++, CUDA/GPU optimization, and kernel-level performance tuning
 </li>
 <li>
 -Experience with reinforcement learning, particularly in systems optimization and decision-making tasks
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer [32985]

Explore 80+ Ai engineer in San Francisco United States this April. Find roles across top companies and apply now to boost your career.