Close | Backend Engineers, Sr. Software Engineer (Marketing) | REMOTE (US) https://close.com/careers

Close is a CRM for small and midsize sales teams (11,000+ paying customers). In 2026 we shipped Chloe, our AI agent that makes sales calls and works inside the CRM.

Backend Engineers (Senior / Staff). Python, Flask/FastAPI, MongoDB, PostgreSQL, Elasticsearch. Two teams: - CRM: agentic enrichment, AI search, making the CRM usable by any MCP agent. Elasticsearch experience is a big plus. - Backend Platforms: a new team building paved roads for our engineers (API patterns, observability, Flask to FastAPI) and guardrails for agent-written code You've shipped LLM features to real users and owned production systems.

Sr. Software Engineer, Marketing. Our first engineer dedicated to close.com (Astro, Sanity, Vercel). You'd own motion and interactivity, performance, SEO, and conversion tracking, and build tools so Marketing can ship without waiting on engineering. 5+ years building marketing sites, with Segment/Amplitude-style analytics.

Prior Labs | Berlin, Freiburg, NYC | ONSITE | Full-time | Technical PM, ML Infra, Research Scientist/Engineer, Backend, Full Stack

We build foundation models for tabular data. Deep learning transformed text and images but mostly skipped tables, which are still the data behind most clinical trials, financial models and scientific experiments. The reason is structural: no natural sequence, no spatial structure, no shared vocabulary across datasets, so the architectures and scaling laws behind LLMs don't transfer.

Our approach: pre-train a transformer on millions of synthetic datasets sampled from causal-structure priors. The whole dataset goes in as context, predictions come out in one forward pass. No per-dataset training, no hyperparameter tuning, seconds instead of hours. TabPFN v2 was published in Nature and set a new state of the art; TabPFN-3 scales to 10M rows. 4M+ downloads, 8k+ GitHub stars, in production from liquid biopsy to rail maintenance. Code: https://github.com/PriorLabs/TabPFN

Since July we're an independent lab inside SAP, with more than EUR 1B committed over four years. Models stay open, research stays public, same team and offices.

Roles (most can sit in any of the three offices):

- Technical Product Manager, Integrations: take every model release live across SAP (AI Core to SAP Analytics Cloud), the cloud marketplaces and customer environments, and help decide which channels we build next. Reports to me, close to the code.

- ML Engineer, Infrastructure: own multi-cluster GPU infra (Slurm on GCP today, multi-provider next), training performance and the tooling layer. We spend tens of millions per year on compute; you own that budget.

- Research Scientist, Foundation Model: drive the model agenda - novel architectures, scaling from 10K to 1M+ samples, multimodal and causal directions. PhD plus top-venue publications, or equivalent.

- Research Engineer, Foundation Model: same agenda from the engineering side. You design experiments, write the training and eval infra, and co-author the papers.

- ML Engineer, Backend: design and scale the backend that serves and finetunes the models. Python/FastAPI, Terraform, K8s.

- Full Stack Engineer, ML Platform: build the product end to end. TypeScript + Python, React/FastAPI/Postgres.

Also hiring: Applied Scientist, Forward Deployed ML Engineer, Research Scientist (Foundational Data Science), PhD research interns, plus GTM and ops roles.

40+ people with backgrounds from Google, DeepMind, Jane Street, Goldman, G-Research, CERN. Led by Frank Hutter, advised by Bernhard Schölkopf and Yann LeCun. Comp competitive with top AI labs.

All roles and applications: https://jobs.ashbyhq.com/prior-labs

Questions welcome in the replies here.

meetyogi.com | Senior Software Engineer, Backend / Product | $180-220k | Hybrid NYC | Series A | 35 headcount, ~10 in engineering

Yogi aggregates and analyzes millions of customer feedback data points from online retailer reviews, social, cx ticketing systems, etc to help companies make better decisions about their products and markets. We operate mostly in CPG, where our customers are household brands you'd recognize, both enterprise and up-and-coming.

--

Everyone is kind and engaged with work at Yogi. It's a nice vibe.

Our stack is pretty standard SaaS - python (fastapi, prefect), postgres/clickhouse, react/typescript web app. The app experience is what you'd expect from a data analytics platform - charting and agentic workflows that generate insights from the data.

In terms of the moment, we're reaching the bounds of some early domain assumptions, while also figuring out how to expand into new ones. On the code front, broadly speaking we're improving quality and process each quarter by an order of magnitude. AI has been a boon for us. (I've personally invested a lot in our dev tooling to make code output high quality and deterministic)

There's a lot of greenfield opportunity and also scale challenges to be solved on existing tech. No shortage of things to do, ownership is as much as you want to take on.

--

Interview process is a chit chat with our CTO, an onsite with a practical coding exercise (not crazy i promise), a system design conversation, and behavioral interview.

Email me at jon.young(at)meetyogi.com or connect w me on linkedin /joncyoungii if you want to learn more. Happy to answer any questions you have honestly and refer you if it makes sense on both ends

CVector | Software Engineers, Senior Research Engineer | New York City (FiDi) | ONSITE | Full-time | VISA SPONSORSHIP

CVector builds software to bring real time economic optimization and AI prediction to every energy and manufacturing plant. We integrate real-time data visualization and analytics to help power generation stations, chemical plants, and other critical infrastructure make informed decisions in rapidly changing environments. You'll help create intuitive, robust web apps, machine learning models and backend systems, shaping tools that directly impact industrial operations and energy reliability. Build AI agent systems that automatically foresee upcoming problems and provide possible solutions.

Full Stack and Backend Software Engineers: We're looking for a passionate Software Engineers comfortable working across our stack (Python, Typescript, React, Supabase, MQTT, TimescaleDB, PostgreSQL, AWS, FastAPI) or someone to specialize in our backend infrastructure.

Senior Research Engineer: Candidates should be experienced with machine learning, and analysis using Python.

Reach out to me at jnapoli+hn@cvector.com

Location: Boston, MA Remote: Yes (preferred) Willing to relocate: No Technologies: Python, TypeScript, Rust, SQL | pandas, polars, Arrow, DuckDB/DataFusion, Parquet, PostgreSQL | React, ag-grid, FastAPI, Django | MCP servers, LLM tool design, agent evals Email: paddy@paddymullen.com

I build data tools, from the dataframe backend to the browser.

I created and maintain Buckaroo (https://github.com/paddymul/buckaroo), an open source dataframe UI for Jupyter, marimo, and VSCode — summary stats and a histogram over every column, across pandas and polars. 683 stars. Scrolling millions of rows without eating the browser took a segment-merging row cache and parquet decoded client side.

Recently: Tallyman, a data science environment for coding agents. Named computations in a dependency DAG, results rendered live in a browser companion, every step keeping the prompt that made it. Demoed at PyData London 2026.

Before that: Flatfile, Attune, Tudor, and Bokeh/Wakari at Anaconda.

Looking for data infrastructure, developer tools, or agent tooling — where a hard backend problem has to surface as something a person can use.

Paramark | Software Engineer (L4) | San Francisco HYBRID (3 days/wk) or REMOTE (US) | Full-time | $199K–$249K + equity

Paramark helps Marketing teams optimize spend across all of their channels and programs. There are proven scientific ways to do this, but they are poorly understood and practiced by only a tiny fraction of teams. Our product ingests data from all of our customers' marketing channels and uses it to train open-source ML models for both measurement and experimentation. This makes it possible for any marketer to use these methods.

In this domain, it's hard to figure out what to build, and it's even harder to be both accurate and simple. You'll be joining a small team -- we have four product engineers. That means owning systems end to end and having real influence over what gets built. Your typical project will start with a high level goal, and you will figure out the rest.

Founded 2023, ~16 people, $8M from Greylock, cash-flow positive. Reasonable working hours: when the Mercury News covered the return of 996 culture, we were the counterexample. "We don't think early stage startup life requires 18-hour days, or even 12-hour days." https://www.mercurynews.com/2025/08/25/silicon-valley-startu.... 4 weeks PTO plus federal holidays, medical/dental/vision (100% of employee premiums, 50% for family).

Looking for 8+ years, full-stack. Some exposure to statistics, experimentation, or A/B testing helps.

Stack: TypeScript, React, Python, Postgres. Google Cloud, Kubernetes, FastAPI, taskiq.

Process: intro call; technical phone screen; one-day onsite in SF (travel covered for remote candidates)

In-person: https://paramark.com/careers/software-engineer-l4

Remote: https://paramark.com/careers/software-engineer-l4-remote

I'm the CTO and I read every application myself. Happy to answer questions in this thread.

VOYGR (YC W26) | Founding Product Engineer | San Francisco | ONSITE | Full-time | $150K-$200K + 0.5%-2.0% equity

I'm Yarik, cofounder and CTO. Before this I spent 20 years in tech with 10+ years running infra, ML and search teams at Google, Meta and Apple.

We love maps and build location/businesses APIs for AI apps and agents. If ChatGPT tells you a restaurant is open and it actually closed in March, that's the problem we fix. We check whether a business still exists, whether its hours and details are right, and enrich it with what's being written about it on the web (news, articles, events). Customers get all of it through one API and we solve it for them with our models which use all available sources and ai voice agents which can confirm the information.

You'd be one of the first engineers. Some weeks that's search and ranking, some weeks it's data pipelines or evals, some weeks it's the API or something a customer asked for yesterday. You'll have a big say in what gets built, not just how.

Stack: Python, FastAPI, Postgres/PostGIS, DynamoDB, Redis, AWS (EKS), our own ML models plus LLM APIs (OpenAI, Gemini, Anthropic).

What I'm looking for: - 2+ years shipping production systems, or fewer if your background is unusual and you can show what you've built - real experience with at least one of: search/IR, large-scale data processing, ML systems, API design - you already use Claude Code, Cursor or similar as part of how you work - geo/POI data experience is a plus, not required

Fair warning: we are a small team, fast pace, and there could be nights and weekends. If that's not where you are in life right now, totally fine, this just isn't a good fit.

Process: a short note on why you, a 30 min call with me and then Vlad, a technical deep dive, then a paid trial project.

Apply here: https://www.workatastartup.com/jobs/93490 or email me directly at yarik@voygr.tech

Hedge (YC) | Founding Engineer | San Francisco | ONSITE | Full-time | $150K-$250K + 1-3% equity

Hedge is an AI-native insurance company. We started as a wholesale brokerage for specialty commercial insurance, where AI agents do most of the work of placing policies: reading messy submissions, chasing missing information, working with 100+ insurance markets, and moving accounts toward coverage. The agents are in production doing real work for paying customers.

We're hiring our founding engineer to own the platform end to end: agents, evals, data pipelines, integrations, and reliability. Python/FastAPI, TypeScript/React, Postgres. You should be deeply technical, resourceful, and have taken something from zero to one. No insurance experience needed.

In office in SF

Apply: https://www.hedgespecialty.com/careers?ashby_jid=b79fa956-bd...

City Detect | Full Stack Product Engineer (Design & Geospatial) | Tuscaloosa, AL | REMOTE (US) | Full-time | $110k–$159k + equity

City Detect uses AI and computer vision to map the physical world for cities. Sensors capture street-level conditions so local governments can find and respond to issues like blight and track how neighborhoods change over time. Founded in 2021, Series A, working with municipalities across Texas, California, Florida, and beyond.

We're looking for a frontend-leaning full stack engineer with a strong eye for design to own the map-heavy parts of our product. That means interactive maps, spatial data explorers and dashboards that city staff use to make decisions.

Stack: React/TypeScript, Python/FastAPI on AWS Lambda, Aurora PostgreSQL + PostGIS. Experience with Mapbox, deck.gl, Leaflet, D3, vector tiles/H3, or nation-scale OSM data is a big plus.

Mid to senior level. Small team, close work with the founders, real ownership.

Process: phone screen, portfolio/design review, 1–2 technical conversations, references, then a chat with our CEO. No LeetCode.

Perks: unlimited PTO, health/dental/vision, $100/mo wellness stipend, team retreats twice a year.

Apply: https://jobs.gem.com/citydetect/am9icG9zdDr5AWjF1AZ1UgSdc0I0... Questions: bjorn@citydetect.com

Location: Dorset, UK

Remote: Yes (UK, US and EU time zones)

Willing to relocate: No

Technologies: Ruby on Rails, Python (FastAPI), TypeScript/Node, Go, PostgreSQL, AWS, Hotwire

Resume/CV: https://wagnermatos.co.uk

Email: wm@wagnermatos.co.uk

Senior engineer, over 15 years. I build complete products: one senior engineer accountable end to end, AI accelerated. Recent work includes a clinical alerting platform used by NHS trusts, an edge to cloud analytics platform for Johnson & Johnson Medical, and the cloud platform behind a fielded detection hardware fleet. Also open to contract engagements. Case studies and client testimonials on the site.