Stanford Research Computing | Stanford, CA (next to Palo Alto) | Full-time | Three positions | ONSITE,HYBRID

Stanford Research Computing (https://srcc.stanford.edu) is a collaboration between University IT and the Vice Provost and Dean of Research. We operate HPC environments for researchers, we do one-time consultations on projects (from software and pipelines, to data management, to physical building design and fit-out), and we provide contract support for individual Labs, Departments, and Schools.

We have three open positions:

• HPC Hardware & Infra Sysadmin [ONSITE]: We are looking for a system administrator to help run the hardware & infrastructure portions of Sherlock, our largest HPC cluster. Sherlock is a mix of Intel & AMD x86_64 servers, with three Infiniband fabrics, plus an Ethernet backbone. You'll be responsible for maintaining, troubleshooting, and improving the hardware of Sherlock. That is, keeping things working, and figuring out how to make it better. More info: https://phxc1b.rfer.us/STANFORDbEHWH7

• Principal Storage Architect & Team Lead [HYBRID]: Our current storage team lead is moving on to Industry, so we're splitting his work into two separate roles. This is the Technical Manager position: You'll be leading the storage team, setting the direction for our large storage environments: Oak (file storage, used by multiple cluster), Fir (fast scratch for Sherlock), and Elm (object storage on top of tape). Knowledge of Lustre, Infiniband, and PB-scale storage is important. More info: https://phxc1b.rfer.us/STANFORD5.1WH8

• Storage Architect or Storage Sysadmin [HYBRID]: This is the second role I referenced above. You'll be maintaining & expanding Oak, our 20+ Pebibyte Lustre storage environment used by our largest HPC clusters. Depending on your experience level, you might also have some responsibility for Elm, which provides object storage on top of tape. Knowledge of Lustre, Infiniband, and PB-scale storage is important here, too. More info: https://phxc1b.rfer.us/STANFORDHPfWHA

If you don't already live in the Bay Area, we provide a relocation incentive. Depending on where you live, we provide free transit passes. Unfortunately, if you drive, you will have to pay for parking for the days you're on-site. There is some on-call around the holidays. We get a 403(b) match, good healthcare, and 30+ days off per year (holidays + vacation). All Benefits are all publicly documented at https://cardinalatwork.stanford.edu/benefits-rewards.

If you have questions, feel free to reply here or email me (the info is in my profile)!

Senior ML Engineer | Ping Data Intelligence | REMOTE or ONSITE (Miami, FL) | Full-Time | https://www.pingintel.com Ping Data Intelligence is a dynamic startup based in Miami, FL, revolutionizing the property insurance sector with cutting-edge web technologies and ML-powered tools. Despite rapid growth, we retain the stability of a self-funded, profitable company. Role Overview: As a Senior ML Engineer at Ping, you will sit at the intersection of research and data engineering — designing, training, and deploying machine learning models that power our property attribute classification, document extraction, and geospatial products. This is a hands-on role for someone who can read a paper in the morning, prototype an idea by lunch, and ship it to production by end of week. You will own ML systems end-to-end: from data pipeline design and feature engineering through model training, evaluation, and production deployment. The role is remote-friendly, with the option to work onsite at our Miami, FL office.

Responsibilities: Design, train, fine-tune, and evaluate ML models (LLMs, classification, sequence models) for property insurance. Build and maintain robust data pipelines that feed training, evaluation, and inference workloads at scale. Develop rigorous evaluation frameworks — establish metrics, build rater alignment processes, and apply statistical methods to determine when a candidate model is genuinely better than production. Run controlled experiments, ablations, and A/B tests; communicate findings clearly with appropriate uncertainty quantification. Deploy models to production and own their performance, drift monitoring, and iteration cycles. Collaborate with the engineering team to integrate ML services into our backend (Django/Python) and frontend (React/TypeScript) products. Stay current with the ML literature and translate relevant advances into practical improvements for our products.

Required:

PhD in Statistics, Machine Learning, Computer Science, Applied Mathematics, or a closely related quantitative field (or equivalent research experience with a strong publication or production track record). Strong foundation in statistics — experimental design, hypothesis testing, Bayesian methods, and uncertainty quantification. Minimum 5 years of combined research and applied ML experience, with a proven track record of shipping models to production. Deep proficiency in Python and the modern ML stack (PyTorch, Hugging Face, scikit-learn, pandas, NumPy). Hands-on experience with LLMs, including fine-tuning (LoRA/QLoRA, full fine-tunes), prompt engineering, and evaluation. Strong data engineering skills — comfort building reliable pipelines over messy real-world data, working with SQL and columnar formats. Excellent debugging, problem-solving, and written communication skills.

Why Join Ping: Work directly on ML systems that touch real production traffic from day one. Collaborate with a small, senior team of insurance and tech veterans building products that are reshaping the property insurance industry. Enjoy the autonomy of a research role with the impact of an applied one — your models will be in production, used by real customers, and you will see the results immediately. Please apply at jobs@pingintel.com

Mercor (YC W23) | San Francisco, CA | Full-Time

We're building the AI layer for global hiring — matching companies with top technical talent and handling everything from evaluation to payroll. We process payments to contractors in 150+ countries and are scaling fast. Backed by Peter Thiel, Jack Dorsey, and others.

Software Engineer, Payments | SF or NYC

https://jobs.ashbyhq.com/mercor/3c02ed8c-3807-4aef-91cc-ccca...

Own the systems that move money across 150+ countries. You'll build and scale Mercor's payments infrastructure — handling global disbursements, reconciliation, and financial reliability at scale. Strong backend chops and interest in fintech systems required.

Infrastructure Engineer | SF or NYC

https://jobs.ashbyhq.com/mercor/296c4031-5e98-4772-95f5-a9eb...

Build and own the infrastructure that powers Mercor's core platform. You'll work across compute, networking, reliability, and developer tooling — keeping a fast-growing system stable and scalable. Ideal for engineers who care deeply about uptime, performance, and platform efficiency.

Software Engineer, Platform | SF or NYC

https://jobs.ashbyhq.com/mercor/cb67851b-0269-4cf5-996c-34c3...

Build the foundational systems that all of Mercor's products rely on — APIs, developer primitives, internal tooling, and shared services. You'll work across teams and have outsized impact on engineering velocity and product quality.

Software Engineer, Fraud | SF or NYC

https://jobs.ashbyhq.com/mercor/4d817fa9-8860-4063-9da7-f484...

Detect and stop fraud on one of the world's largest talent marketplaces. You'll build real-time signals, risk models, and enforcement systems to protect the integrity of Mercor's platform — balancing precision with a great experience for legitimate users.

Data Engineer | SF or NYC https://jobs.ashbyhq.com/mercor/7d9d9439-848b-4fb4-b276-9efc...

Build the data infrastructure that powers Mercor's matching, evaluation, and business intelligence systems. You'll design and own pipelines, warehousing, and data models that inform both product and operations at scale.

Software Engineer, Agents | SF or NYC https://jobs.ashbyhq.com/mercor/4f4fc8c3-4056-47bb-9e00-1db6...

Build the agentic systems at the core of Mercor's product — autonomous pipelines that evaluate candidates, match talent, and take actions on behalf of users. You'll work at the intersection of LLMs, product, and infrastructure to ship AI-native features.

DuckDuckGo | Multiple Roles | Remote | Full-time | $178,500 - $242,800 USD + equity

We are looking for candidates that are excited to join us on a mission to raise the standard of trust online. All of our roles are fully-remote, except where specific locations are noted.

Most of the software engineering positions have been repeating here for years because we've been continually hiring for them, scaling our whole team to now over 300 people—many of those hires have come through Hacker News. We've been improving our hiring process over time, and we know some good candidates may have fallen through the cracks. Some people who tried in the past have had success going through it again, and we still pay for hiring projects.

Engineering Director, Backend - $242,800 USD + equity https://jobs.ashbyhq.com/duck-duck-go/3be5b69c-bacc-48fb-941...

Senior Backend Engineer - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/53022b02-da3d-4fda-827...

Senior Android Engineer - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/57eea673-2519-4afc-a9a...

Senior iOS Engineer - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/a1239b43-0c9a-45a4-b35...

Senior Software Engineer - Windows Desktop App - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/47e569c6-f995-4955-a89...

Senior Data Scientist - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/a447e823-fd8f-438f-909...

Director, Data Science - $242,800 USD + equity https://jobs.ashbyhq.com/duck-duck-go/0269aeaa-8d8f-4c8d-b78...

Senior Legal Counsel - Subscriptions & Marketing - $178,500 USD + equity https://jobs.ashbyhq.com/duck-duck-go/4ebedcfb-c89f-4cab-bf1...

and MORE: https://duckduckgo.com/careers

Cloudflare | Systems or ML Engineer, Workers AI | Austin, TX or London, UK or San Francisco, CA (Hybrid) | Full-Time | https://cloudflare.com

Cloudflare is building across the entire AI stack. Here are some exciting things that we have launched recently:

- Kimi k2.5: https://blog.cloudflare.com/workers-ai-large-models/

- Kimi Performance Improvements: https://blog.cloudflare.com/high-performance-llms/

- Kimi k2.6 Speculative Decoding and Shared KV Cache: https://x.com/kevin_flansburg/status/2050238819065299110

- Unweight Tensor Compression: https://blog.cloudflare.com/unweight-tensor-compression/

- Code Mode MCP Servers: https://blog.cloudflare.com/code-mode/

- Agents SDK: https://blog.cloudflare.com/building-agents-with-openai-and-...

- Agent Memory: https://blog.cloudflare.com/introducing-agent-memory/

- Internal AI Tooling: https://blog.cloudflare.com/internal-ai-engineering-stack/

- Release Cog v0.19: https://github.com/replicate/cog/releases/tag/v0.19.0

- Dynamic Worker Sandboxes: https://blog.cloudflare.com/dynamic-workers/

- Dynamic Workflows: https://blog.cloudflare.com/dynamic-workflows/

We are looking for systems and ML engineers to help build our edge inference platform:

- Senior Systems Engineer, Workers AI - https://job-boards.greenhouse.io/cloudflare/jobs/7764827?gh_...

- Senior / Principal Machine Learning Engineer, Workers AI- https://job-boards.greenhouse.io/cloudflare/jobs/6297179?gh_...