VLM Run – Founding ML Systems Engineer / Researcher

We're building bleeding-edge infrastructure for Vision Language Models (VLMs). Join us as a founding engineer to reimagine the visual AI infrastructure layer for enterprises.

📍 Location: Santa Clara, CA (3+ days/week)
🧠 Roles: ML Systems Engineer & Applied ML/CV Researcher
💰 Comp: $150K – $220K + 0.5 – 3% equity
📬 Apply: hiring@vlm.run with GitHub + standout work

🧱 What We’re Building

VLM Run is a horizontal platform to fine-tune, serve, and specialize VLMs with structured JSON outputs — for docs, images, video, and beyond.

Think of it as the orchestration layer for next-gen visual agents — built on a developer-friendly API and production-grade runtime.

We're tackling: - Fast inference: High-throughput, low-latency inference for multimodal ETL (vLLM-style, but for visual content like images, videos, streaming content) - Fine-tuning infra: Scalable fine-tuning and distillation for structured, multi-modal tasks (OCR++, layout parsing, video QA) - Compiler infra: All kinds of optimizations to make our GPUs go brrr (OpenAI Triton kernels, speculative/guided decoding etc)

We’re early — you’ll define the infrastructure backbone of VLMs in production.

💡 Why This Matters

Most VLMs are stuck in demos — slow, flaky, and hard to deploy.

We're fixing that with: - Developer-native APIs (not chat-based hacks) - Structured JSON outputs for automation - Fast, predictable inference on non-text modalities

You'll work on core ML systems — not glue code — with full ownership over compiler paths, serving infra, and fine-tuning pipelines.

👩‍💻 What You’ll Do

You'll shape the future of how VLMs are trained, served, and used in production. Your work could include: - Building low-latency runtimes and speculative decoders - Shipping distillation pipelines that power real-time visual agents - Designing APIs that make visual data programmable for developers

✅ You Might Be a Fit If:

• Built or optimized ML compilers, kernels, or serving infra (Triton, vLLM, TVM, XLA, ONNX)
• Deep PyTorch/HuggingFace experience; trained ViTs or LLaMA/Qwen-class models
• 2+ YOE post-MS or 4+ YOE post-BS in ML infra, CV systems, or compiler teams
• Bonus: Published OSS or papers, shipped SaaS infra, or scaled training/serving infra

🌎 Logistics

• Compensation: $150K – $220K + 0.5 – 3% equity
• In-Person: 3+ days/week in Santa Clara, CA
• Benefits: Top-tier healthcare, 401K, early ownership

🔗 Apply Now

📧 hiring@vlm.run
🌐 www.vlm.run
💼 LinkedIn

📎 Send GitHub, standout projects, or a quick note on why this is a fit.

Let’s build the future of visual intelligence — fast, structured, and programmable.

New York, NY

The Research Engineering team is dedicated to accelerating the velocity of machine learning research and expanding the exploration space for innovations at PDT. We partner with PDT’s quantitative researchers to design and build a state-of-the-art environment for testing ideas rapidly and efficiently.

Research at PDT requires significant compute, and as such, we are looking for a talented engineer with in-depth knowledge of ML techniques and DL ecosystem to help us build the infrastructure capable of supporting complex scientific research at scale.

This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week.

Why join us?  PDT Partners has a stellar 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world. PDT’s exceptional employee-retention rate speaks for itself. Our people are intellectually curious, collaborative, down-to-earth, and diverse.

Responsibilities:

Partner with the research team to understand future research directions and build the next generation of highly scalable infrastructure for alpha, signal, and portfolio construction. Incorporate advancements in machine learning, hardware accelerators and high-performance computing to optimize research workflows. Maintain, develop, and re-imagine the extensive internal research stack that continues to be a differentiating factor for PDT business.  Optimize models for inference and use in real time trading systems.

Below is a list of skills and experiences we think are relevant. Even if you don’t think you’re a perfect match, we still encourage you to apply because we are committed to developing our people.

Experience with building infrastructure for training/fine-tuning large ML models. Intellectual curiosity and a strong interest in solving difficult problems. Exceptional programming skills and proficiency in identifying performance bottlenecks. Experience with the python scientific stack and DL libraries (PyTorch, Tensorflow, etc.) Experience with hardware accelerators. Previous experience in Quant Finance is not required.

The salary range for this role is between $190,000 and $250,000. This range is not inclusive of any potential bonus amounts. Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.

PRIVACY STATEMENT: For information on ways PDT may collect, use, and process your personal information, please see PDT’s privacy notices.

San Francisco, California & Seattle, Washington

Are you a charismatic data engineering Developer Advocate at heart, someone who excels in the spotlight, loves presenting and hosting events, and possesses a deep knowledge of the Databricks Intelligence Platform?

As a Databricks Developer Advocate, you’ll be a crucial link between our engineering teams and the broad community of data professionals building their careers on Databricks technologies. This role will leverage your strong expertise in Databricks to educate, inspire, and support our growing user base.

Your responsibilities will encompass a wide range of knowledge-sharing activities. You’ll deliver engaging talks, host insightful panels and meetups, create informative blogs and video content, develop comprehensive courseware, provide expert answers in community forums, and conduct one-on-one sessions with influential data engineers and scientists. These efforts will help disseminate best practices and foster a thriving Databricks community.

Community engagement will be at the heart of your role. You’ll work closely with the Databricks community and the product and engineering teams, ensuring that user needs and product development align seamlessly. Reporting directly to the Head of Developer Relations, you’ll collaborate with fellow developer advocates and program managers to create and execute a cohesive and impactful developer relations strategy.

The ideal candidate for this position will embody the values of our Developer Relations team: a deep passion for data and AI, genuine empathy and technical understanding of developers’ needs, and a strong commitment to effectively explaining our products.

You’ll use your diverse Databricks skill set to educate the community about Databricks technologies and continuously gather and utilize community feedback to improve the developer experience.

The impact you will have:

- Create compelling content to inspire data practitioners, helping them discover new features and run projects at scale.
- Drive awareness and adoption of Databricks technologies through speaking engagements at industry events.
-Create high-quality educational content like videos, sample notebooks, datasets, tutorials, courseware, and blog posts.
- Expand and nurture the Databricks user community by organizing and growing meetups and user groups and providing support to data scientists, engineers, and analysts in online communities.
- Collaborate with product and engineering teams to share community learnings and influence product direction.
- Create and manage developer-focused programs to foster engagement and loyalty, creating a positive developer experience for data practitioners.
-Gather and analyze feedback from the community to drive continuous improvement of Databricks products and services.

What we look for:

- 5+ years experience as DevRel and as a software developer, solutions architect, or related profession
- Subject matter knowledge of solving data engineering problems at all scales.
- Active participation and recognized leadership in Databricks community forums, chats, and meetups
- Comprehensive understanding of the Databricks products and ecosystem
- Proven track record in nurturing developer communities, organizing user groups, and facilitating global meetups
- Exceptional communication skills, with a talent for articulating complex concepts through writing, teaching, videos, and public speaking
- Deep empathy for developer needs, with the ability to craft engaging experiences across tutorials, notebooks, and community platforms
- Adept at collaborating with cross-functional stakeholders to align community initiatives with product objectives
- Demonstrated ability to catalyze growth in both digital and in-person developer communities

SF Bay Area or New York City

About the role We’re looking for seasoned ML Infrastructure engineers with experience designing, building and maintaining training and serving infrastructure for ML research.

Responsibilities:

Provide infrastructure support to our ML research and product

Build tooling to diagnose cluster issues and hardware failures

Monitor deployments, manage experiments, and generally support our research

Maximize GPU allocation and utilization for both serving and training

Requirements:

4+ years of experience supporting the infrastructure within an ML environment

Experience in developing tools used to diagnose ML infrastructure problems and failures

Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage)

Experience working with GPUs

Nice to have

Experience with large GPU clusters and high-performance computing/networking

Experience with supporting large language model training

Experience with ML frameworks like Pytorch/TensorFlow/JAX

Experience with GPU kernel development