I lead the A3 Lab at Aarhus University and are hiring a Three-year PhD in Physical AI; onsite in Aarhus, Denmark.
Topics: Vision–language–action models, world models, reliable adaptation and efficient AI, RL. Background: Relevant master’s degree and strong Python/PyTorch experience. Deadline: 1 November 2026. Start: January 2027 or later. Contact: behzad@ece.au.dk. Official application link: https://phd.tech.au.dk/for-applicants/apply-here/saeropslag/...
Flow Traders | Research Engineer | Hong Kong | Full Time | Visa | Relocation Flow Traders is a leading proprietary trading firm with an entrepreneurial and innovative Tech culture at the heart of its business. We are looking for Research Engineers in our Hong Kong office. Join us build and scale the research framework behind our systematic trading models. You’ll work closely with Quantitative Researchers, drive end‑to‑end ML pipelines, and shape global standards for data‑driven model development. Research Engineers have joint responsibility for conducting research and delivering models. You’ll thrive if you have: - 8+ years in ML / Data Science / Research Engineering (Postdoc/Faculty can count towards this); - Strong Python and libraries such as Ray, numpy, PyTorch, and pandas; - Solid math/stats background; - Experience with modern dev practices & cloud technologies. If you're interested, apply here: https://www.flowtraders.com/careers/job-description/7431246
Flow Traders | C++ Senior Software Engineer | Hong Kong | Full Time | Visa | Relocation We are looking for a Senior C++ Software Engineer, you'll help design and optimize next-generation market data and execution platforms powering systematic trading across hundreds of venues. The role covers high performance market data ingestion and order execution, building and optimizing trading systems. To succeed you will need to have: - 5+ years of C++ experience in HFT/ financial sector -Strong knowledge in one or more APAC markets If you are interested, apply here: https://www.flowtraders.com/careers/job-description/8212740
Or if you'd like to see other roles at Flow Traders, please check our careers website: https://flowtraders.com/careers/
SentiLink | https://www.sentilink.com/ | Engineering & Data Science | REMOTE, HYBRID, and ONSITE (UNITED STATES ONLY) | Full Time
Primarily hiring in the U.S. for more senior level roles.
We’re hiring across Engineering (Primarily Backend/Data Platform) and Data Science / ML roles. Hiring at Manager/Director level as well as Senior IC levels. We’re language-agnostic and hire for fundamentals.
Across the team you’ll see: • Python, Go, Rust, Scala • PostgreSQL, Snowflake • Kafka, Redis • Terraform, Kubernetes • ML: XGBoost, PyTorch, Feature stores, real-time scoring pipelines
If you love solving complex distributed systems challenges, building customer-facing ML products, or working on detection systems that must be both high-precision and low-latency, you’ll fit right in.
Roles are here: https://jobs.ashbyhq.com/sentilink?utm_source=hacker_news If you have questions, feel free to reach out directly at liz.woodfield at sentilink dot com.
At SentiLink, we stop identity fraud at scale. Our products protect banks, fintechs, marketplaces, and leading financial institutions from synthetic identity fraud, identity theft, and emerging threat. We analyze millions of applications while keeping real users moving fast.
We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.
SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design.
We’re a small, high-impact team solving one of the most interesting and adversarial problems in fintech: how do you build systems that reliably determine whether a real human is on the other side of a financial transaction?
ML6 | Senior AI Engineer | Python, TensorFlow, PyTorch, GCP, AWS, Azure | Full-time | Amsterdam, Berlin, Munich, Eindhoven, Ghent (EU) On-site/hybrid
We are an AI engineering company that builds end-to-end AI solutions. By applying the latest AI research, we keep our clients at the forefront of innovation. If you are interested check out:
https://www.ml6.eu/en/customers/cases/
Work on innovative projects for the biggest clients across Europe such as Randstad, ASML, FUNKE, and many more! Whether it’s about leveraging LLMs to improve customer support, building data lakes on cloud platforms to improve storage or implementing models using sensor data for quality control. You can find it all at ML6. You will mostly work with Python and a range of ML frameworks such as TensorFlow, PyTorch, or HuggingFace Transformers and help bring application into production by building data pipelines and cloud infrastructure on all of the major cloud providers (GCP, AWS, Azure).
Open roles include:
• Senior AI Engineer
• Senior Software Engineer
• Medior AI Engineer
• Squad Lead GenAI
and many more!
Apply now at https://jobs.ml6.eu/
Rebar | Software Engineers (Product, Applied AI, ML Infra, Data Platform) | ONSITE 5 days/week, New York City (union square area!) | Full-time | $150k–$260k + equity | https://jobs.ashbyhq.com/rebar
We build AI estimating software for commercial HVAC, plumbing, and electrical contractors. Before bidding on a job, a contractor or estimator has to count every duct, fitting, diffuser, and piece of equipment across a set of construction drawings that can run to thousands of pages. We speed this up by ingesting the drawings, detecting the equipment schedules, finding symbols, and producing a priced takeoff that the estimator reviews and corrects in a collaborative canvas editor. We have strong PMF and raised a $14M Series A earlier this year.
It may not sound sexy, but it actually is!! There are a ton of hard and interesting engineering challenges. Just to highlight a few:
* very dense document drawings with a realtime collaborative canvas editor (think 50k DOM elements and up) * segmentation models (and many more) whose output has to become geometry a user can interact with * gpu inference across hundreds of concurrent jobs * dynamic analytics and chart generation from agentic workflows custom built for estimators
Open roles:
* Software Engineer, Product ($180k–$240k): https://jobs.ashbyhq.com/rebar/5ab49c2d-9a70-4723-9217-7704a... * Software Engineer, Applied AI ($150k–$250k): https://jobs.ashbyhq.com/rebar/ad41a627-d9a4-49a4-a1b4-f7202... * Software Engineer, ML Infrastructure ($200k–$260k): https://jobs.ashbyhq.com/rebar/ead8df0c-b6da-4e79-90d0-99651... * Software Engineer, Data Platform ($170k–$220k): https://jobs.ashbyhq.com/rebar/c227ea05-98f8-4a08-9760-f7e3c...
Stack: TypeScript/React/Next.js, Python, PyTorch, Postgres, Temporal, AWS, Kubernetes, Modal.
We're also hiring for PMs, implementation, sales, and marketing roles! I'm the Head of Engineering. Apply through Ashby and mention HackerNews or HN in the Ashby form. Or email me at john@withrebar.ai. We will reply to everyone, but it might take us some time! Thank you in advance for your patience
Additionally, there's a fun puzzle on our marketing site that will fast track your application if you want to solve!
River | Staff Engineers (Elixir) | NYC or REMOTE (US, Europe, South America) | Full-Time | $200K-$250K + equity | https://jobs.ashbyhq.com/river?utm_source=Zp9nJyqvd4 I'm Alex, founder and CEO of River. I also wrote the first line of code and still ship PRs.
River is a client-first Bitcoin-only financial institution building the financial app people use every day to save in bitcoin and spend in dollars. We custody over 33,000 BTC, serve individuals and businesses across the U.S., and are profitable. We publish cryptographic proof of reserves monthly and our company financials annually.
Here's what our engineering team is working on:
- Real-time Bitcoin and USD payments, trading, and settlement on an Elixir monolith with a unified GraphQL API
- Next-generation Bitcoin custody with quorum signing, key ceremonies, and geo-redundant infrastructure
- Scaling our ML/AI systems (Python, PyTorch, XGBoost, LLMs) to automate operations and tackle fraud/risk
- A ground-up React and React Native rewrite of our consumer app
- Porting our Lightning Network infrastructure from Go into Elixir
Apply at https://jobs.ashbyhq.com/river/610f652b-bdb9-4d82-9973-680ba...
Location: Pisa, Italy (CET) Remote: Yes, remote only Willing to relocate: No Technologies: Python, LLM/agent orchestration, local embeddings, retrieval evaluation, AWS (Lambda/SQS/EventBridge), Terraform, Django, PostgreSQL, LightGBM/PyTorch, NLP/Transformers Résumé/CV: linkedin.com/in/vslovik Code: github.com/vslovik/fenix — local-embedding search whose relevance is actually measured: labelled control probes, blinded human ranking, precision@k. No API keys. Email: valeriya.slovikovskaya@gmail.com
Software architect, 15+ years in production systems, almost entirely startups and internal startups — fintech, e-commerce, pharma, publishing.
The work I get pulled into is the recurring startup problem: a service shipped fast under launch pressure, without adequate tests, that later has to be made reliable without being stopped. Incident response, re-architecture, and the release discipline that keeps it from happening again. Most recently that has meant a regulated UK consumer-credit platform — loan servicing, arrears, forbearance, statutory breathing space, and early-settlement calculations written against consumer-credit legislation. Regulation as code, behind a test suite larger than the production codebase.
I've done that in all three configurations: taking a core system from problem statement to release, leading the team that carried it (1 to 7 engineers in ten months), and now doing the same work again with agentic tooling covering what the team used to.
On the data side: a LightGBM acquisition model over a 38M-row base — 0.77 test AUC, 8x lift in the top 1% — scoring 2.9M households for a live campaign. The part I'd rather be judged on is what happened next: I found a validation-set defect in my own pipeline (early stopping on the test split), quantified its effect across every figure I had already reported, restated them, and added a pure-noise regression test that pins the model to chance when fed random features — so that class of leak cannot come back quietly. NLP is hands-on rather than API-deep: my degree thesis fine-tuned BERT, RoBERTa and XLNet to state of the art on the FNC-1 stance-detection benchmark, published at LREC 2020.
Building on my own time: github.com/vslovik/fenix — it ranks an incoming stream against a free-text description of what you're looking for, and answers questions over the same corpus with citations back to source chunks. Ollama embeddings, sqlite-vec, no API keys. The part worth looking at is the evaluation: the ranking anchor is scored against a labelled probe set with a deliberate control group of things I don't want, and live results are rated blind — scores hidden, order shuffled — so the human judgement stays independent of the ranking it is judging. Doing that produced a measured finding I did not expect: an embedding has no notion of negation, so naming a technology in order to reject it moves the anchor toward it. Numbers and method in lessons/embedding-anchors.md.
Also a tool-calling agent that turns unstructured regulatory text into a deterministic calculation pipeline — the model does the extraction, a deterministic engine does the arithmetic.
Looking for agentic AI/LLM engineering, LLM evaluation and observability, AI integration, or software architecture. Founding-engineer shape suits me — early employee, not co-founder, but early enough to be in the room where the work gets defined. Direct with the company that owns the product: not consultancy, not agency placement, not a body on someone else's engagement.